Talking Head (3D)

Demo Videos

All the demo videos are real-time screen captures from a Chrome browser running the TalkingHead test web app without any post-processing.

Video | Description --- | --- | Having a good hair day! – A two-part introduction to the TalkingHead's dynamic bones feature 🦴🦴 and built-in physics engine. Using custom models with rigged hair and two different hairstyles. See Appendix E for more details. | I chat with Jenny and Harri. The close-up view allows you to evaluate the accuracy of lip-sync in both English and Finnish. Using GPT-3.5 and Microsoft text-to-speech. | A short demo of how AI can control the avatar's movements. Using OpenAI's function calling and Google TTS with the TalkingHead's built-in viseme generation. | Michael lip-syncs to two MP3 audio tracks using OpenAI's Whisper and TalkingHead's speakAudio method. He kicks things off with some casual talk, but then goes all out by trying to tackle an old Meat Loaf classic. 🤘 Keep rockin', Michael! 🎤😂 | Julia and I showcase some of the features of the TalkingHead class and the test app including the settings, some poses and animations.

Use Case Examples

Some featured videos, apps, and projects using the TalkingHead class:

Video/App | Use Case --- | --- | Human-AI group conversations. Researchers from UVA, Google, Northeastern, Google DeepMind, and Google Research developed DialogLab, a toolkit to author, simulate and test human-AI group conversations. 🤖🤖🤖 | Video conferencing. A video conferencing solution with real-time transcription, contextual AI responses, and voice lip-sync. The app and demo, featuring Olivia, by namnm 👍 | Fully in-browser AI you can talk to. Uses TalkingHead, HeadTTS (with Kokoro), whisper-web, and WebLLM (with Llama 3.2). No APIs, no accounts. For best performance and WebGPU support, use a desktop version of Chrome or Edge: 👉 EdgeSpeaker.com | Recycling Advisor 3D. Snap a photo and get local recycling advice from a talking avatar. My entry for the Gemini API Developer Competition. | Live Twitch adventure. Evertrail is an infinite, real-time generated world where all of your choices shape the outcome. Video clip and the app by JPhilipp 👏👏NEWS: Featured at the AI Film Awards during the 2025 Cannes Film Festival! | Quantum physics using a blackboard. David introduces us to the CHSH game and explores the mystery of quantum entanglement. For more information about the research project, see CliqueVM. | Interactive Portfolio. Click the image to open the app, where you can interview the virtual persona of its developer, AkshatRastogi-1nC0re 👋 | Interactive Dating Profiles. ❤️ Researchers from the MIT Media Lab and Harvard used the TalkingHead class and data-driven AI to create digital twins that potential dating partners could interact with. Their paper (Baradari et al., 2025) was presented at CHI 2025 in Japan.

More projects, sites and research using TalkingHead:

Link | Description --- | --- Cancer Clinical Trial Participation | Researchers at the University of Florida explored how multiple virtual agents can help overcome barriers to joining cancer clinical trials. TalkMateAI | Real-time Voice-Controlled 3D Avatar with Multimodal AI. Riverts | A platform for building, running, and analyzing interactive user-avatar conversations. Interactive Avatar | Interactive avatars as a service - an easy way to add an AI-driven avatar on your website. Alter egos alter engagement | Researchers at the University of Florida used TalkingHead to explore how embodied AI chatbots can support mental well-being.

Introduction

Talking Head (3D) is a browser JavaScript class featuring a 3D avatar that can speak and lip-sync in real-time. The class supports Ready Player Me / PlayerZero full-body 3D avatars (GLB) and Mixamo / RPM animations (FBX). It also knows a set of emojis and can convert them into facial expressions.

You can create your own 3D avatar for free using the Ready Player Me or PlayerZero service. Alternatively, you can create a custom 3D avatar by making it compatible with RPM models. See Appendix A for more details.

By default, the class uses Google Cloud TTS for text-to-speech and has a built-in lip-sync support for English, German, French, Finnish, and Lithuanian. New lip-sync languages can be added by creating new lip-sync language modules.

It is also possible to integrate the TalkingHead class with any external TTS service that can provide word-level timestamps, such as the ElevenLabs WebSocket API. Note that a lip-sync language module is not required if your TTS engine can output viseme IDs or blend shape data directly. For example, by using the Microsoft Azure Speech SDK, you can extend TalkingHead's lip-sync support to 100+ languages.

The class uses ThreeJS / WebGL for 3D rendering.

[!TIP] If you're looking for a free English TTS that can output timestamps and viseme IDs, check out HeadTTS. It offers Kokoro neural voices, phoneme-level timestamps, and can run locally or even entirely in a browser using WebGPU. And best of all, it's fully compatible with the TalkingHead class.

Talking Head class

You can download the TalkingHead modules from releases (without dependencies). Alternatively, you can install them from NPM, or import all the needed modules from a CDN:

<script type="importmap">
{ "imports":
  {
    "three": "https://cdn.jsdelivr.net/npm/[email protected]/build/three.module.js/+esm",
    "three/addons/": "https://cdn.jsdelivr.net/npm/[email protected]/examples/jsm/",
    "talkinghead": "https://cdn.jsdelivr.net/gh/met4citizen/[email protected]/modules/talkinghead.mjs"
  }
}
</script>

[!TIP] FOR HOBBYISTS: If you're just looking to experiment on your personal laptop without dealing with proxies, JSON Web Tokens, or Single Sign-On, take a look at the minimal code example. Simply download the file, add your Google TTS API key, and you'll have a basic web app template with a talking head.

If you want to use the built-in Google TTS and lip-sync using Single Sign-On (SSO) functionality, give the class your TTS proxy endpoint and a function from which to obtain the JSON Web Token needed to use that proxy. Refer to Appendix B for one way to implement JWT SSO.

import { TalkingHead } from "talkinghead";

// Create the talking head avatar
const nodeAvatar = document.getElementById('avatar');
const head = new TalkingHead( nodeAvatar, {
  ttsEndpoint: "/gtts/",
  jwtGet: jwtGet,
  lipsyncModules: ["en", "fi"],
  mixerGainSpeech: 3
});

Option | Description | Default --- | --- | --- jwsGet | Function to get the JSON Web Token (JWT). See Appendix B for more information. | null ttsEndpoint | Text-to-speech backend/endpoint/proxy implementing the Google Text-to-Speech API. | null ttsApikey | If you don't want to use a proxy or JWT, you can use Google TTS endpoint directly and provide your API key here. NOTE: I recommend that you don't use this in production and never put your API key in any client-side code. | null ttsLang | Google text-to-speech language. | "fi-FI" ttsVoice | Google text-to-speech voice. The used voice must support SSML and <mark> tags that are needed to get word-level timestamps. Currently, Google supports SSML and <mark> tags when using Standard, Wavenet, Neural2, News, or Casual voice types. | "fi-FI-Standard-A" ttsRate | Google text-to-speech rate in the range [0.25, 4.0]. | 1.0 ttsPitch | Google text-to-speech pitch in the range [-20.0, 20.0]. | 0 ttsVolume | Google text-to-speech volume gain (in dB) in the range [-96.0, 16.0]. | 0 ttsTrimStart | Trim the viseme sequence start relative to the beginning of the audio (shift in milliseconds). | 0 ttsTrimEnd | Trim the viseme sequence end relative to the end of the audio (shift in milliseconds). | 400 mixerGainSpeech | The amount of gain for speech. See Web Audio API / GainNode for more information. | null mixerGainBackground | The amount of gain for background audio. See Web Audio API / GainNode for more information. | null lipsyncModules| Lip-sync modules to load dynamically at start-up. Limiting the number of language modules improves the loading time and memory usage. | ["en", "fi", "lt"] lipsyncLang| Lip-sync language. | "fi" pcmSampleRate | PCM (signed 16bit little endian) sample rate used in speakAudio in Hz. | 22050 modelRoot | The root name of the armature. | Armature modelPixelRatio | Sets the device's pixel ratio. | 1 modelFPS | Frames per second. Note that actual frame rate will be a bit lower than the set value. | 30 modelMovementFactor | A factor in the range [0,1] limiting the avatar's upper body movement when standing. | 1 dracoEnabled | If true, use Draco geometry compression. [≥v1.5] | false dracoDecoderPath | Draco decoder library path. [≥v1.5] | "https://www.gstatic.com/draco/v1/decoders/" cameraView | Initial view. Supported views are "full", "mid", "upper" and "head". | "full" cameraDistance | Camera distance offset for initial view in meters. | 0 cameraX | Camera position offset in X direction in meters. | 0 cameraY | Camera position offset in Y direction in meters. | 0 cameraRotateX | Camera rotation offset in X direction in radians. | 0 cameraRotateY | Camera rotation offset in Y direction in radians. | 0 cameraRotateEnable | If true, the user is allowed to rotate the 3D model. | true cameraPanEnable | If true, the user is allowed to pan the 3D model. | false cameraZoomEnable | If true, the user is allowed to zoom the 3D model. | false lightAmbientColor | Ambient light color. The value can be a hexadecimal color or CSS-style string. | 0xffffff lightAmbientIntensity | Ambient light intensity. | 2 lightDirectColor | Direction light color. The value can be a hexadecimal color or CSS-style string. | 0x8888aa lightDirectIntensity | Direction light intensity. | 30 lightDirectPhi | Direction light phi angle. | 0.1 lightDirectTheta | Direction light theta angle. | 2 lightSpotColor | Spot light color. The value can be a hexadecimal color or CSS-style string. | 0x3388ff lightSpotIntensity | Spot light intensity. | 0 lightSpotPhi | Spot light phi angle. | 0.1 lightSpotTheta | Spot light theta angle. | 4 lightSpotDispersion | Spot light dispersion. | 1 avatarMood | The mood of the avatar. Supported moods: "neutral", "happy", "angry", "sad", "fear", "disgust", "love", "sleep". | "neutral" avatarMute| Mute the avatar. This can be helpful option if you want to output subtitles without audio and lip-sync. | false avatarIdleEyeContact | The average proportion of eye contact while idle in the range [0,1]. | 0.2 avatarIdleHeadMove | The average proportion of head movement while idle in the range [0,1]. | 0.5 avatarSpeakingEyeContact | The average proportion of eye contact while speaking in the range [0,1]. | 0.5 avatarSpeakingHeadMove | The average proportion of head movement while speaking in the range [0,1]. | 0.5 avatarIgnoreCamera | If set to true, makes the avatar to ignore the camera and speak to whatever it is facing. | false listeningSilenceThresholdLevel | Silence detection threshold in the range of [0,100]. If the volume stays below the level for the set duration, a "stop" event is triggered. | 40 listeningSilenceThresholdMs | Silence detection duration in milliseconds. If the volume stays below the level for the set duration, a "stop" event is triggered. | 2000 listeningSilenceDurationMax | Maximum silence in milliseconds before "maxsilence" event is triggered. | 10000 listeningActiveThresholdLevel | Activity detection threshold in the range of [0,100]. If the volume stays above the set level for the set duration, a "start" event is triggered. | 90 listeningActiveThresholdMs | Activity detection duration in milliseconds. If the volume stays above the set level for the set duration, a "start" event is triggered. | 400 listeningActiveDurationMax | Maximum activity in milliseconds before "maxactive" event is triggered. | 240000 avatarOnly | If true, creates an avatar armature object instead of a standalone instance with a 3D scene, lights, and renderer. Read Appendix H for more details about the avatarOnly mode. (EXPERIMENTAL) | false avatarOnlyCamera | In avatarOnly mode, sets the camera to which the avatar is linked. | null avatarOnlyScene | If set in avatarOnly mode, the armature object is automatically added to the specified scene. | null update | Custom callback function inside the requestAnimationFrame animation loop. Enables the app to do custom processing before rendering the 3D scene. If null, disabled. | null statsNode | Parent DOM element for the three.js stats display. If null, don't use. | null statsStyle | CSS style for the stats element. If null, use the three.js default style. | null

Once the instance has been created, you can load and display your avatar. Refer to Appendix A for how to make your avatar:

// Load and show the avatar
try {
  await head.showAvatar( {
    url: './avatars/brunette.glb',
    body: 'F',
    avatarMood: 'neutral',
    ttsLang: "en-GB",
    ttsVoice: "en-GB-Standard-A",
    lipsyncLang: 'en'
  });
} catch (error) {
  console.log(error);
}

An example of how to make the avatar speak the text on input text when the button speak is clicked:

// Speak 'text' when the button 'speak' is clicked
const nodeSpeak = document.getElementById('speak');
nodeSpeak.addEventListener('click', function () {
  try {
    const text = document.getElementById('text').value;
    if ( text ) {
      head.speakText( text );
    }
  } catch (error) {
    console.log(error);
  }
});

Method | Description --- | --- showAvatar(avatar, [onprogress=null]) | Load and show the specified avatar. The avatar object must include the url for GLB file. Optional properties are body for either male M or female F body form, lipsyncLang, lipsyncHeadMovement, baseline object for blend shape baseline, modelDynamicBones for dynamic bones (see Appendix E), ttsLang, ttsVoice, ttsRate, ttsPitch, ttsVolume, avatarMood, avatarMute, avatarIdleEyeContact, avatarSpeakingEyeContact, avatarListeningEyeContact, and avatarIgnoreCamera. setView(view, [opt]) | Set view. Supported views are "full", "mid", "upper" and "head". The opt object can be used to set cameraDistance, cameraX, cameraY, cameraRotateX, cameraRotateY. setLighting(opt) | Change lighting settings. The opt object can be used to set lightAmbientColor, lightAmbientIntensity, lightDirectColor, lightDirectIntensity, lightDirectPhi, lightDirectTheta, lightSpotColor, lightSpotIntensity, lightSpotPhi, lightSpotTheta, lightSpotDispersion. speakText(text, [opt={}], [onsubtitles=null], [excludes=[]]) | Add the text string to the speech queue. The text can contain face emojis. Options opt can be used to set text-specific lipsyncLang, ttsLang, ttsVoice, ttsRate, ttsPitch, ttsVolume, avatarMood, avatarMute. Optional callback function onsubtitles is called whenever a new subtitle is to be written with the parameter of the added string. The optional excludes is an array of [start,end] indices to be excluded from audio but to be included in the subtitles. speakAudio(audio, [opt={}], [onsubtitles=null]) | Add a new audio object to the speech queue. In audio object, property audio is either AudioBuffer or an array of PCM 16bit LE audio chunks. Property words is an array of words, wtimes is an array of corresponding starting times in milliseconds, and wdurations an array of durations in milliseconds. If the Oculus viseme IDs are known, they can be given in optional visemes, vtimes and vdurations arrays. The object also supports optional timed callbacks using markers and mtimes. In addition, you can provide an optional anim as an animation template object that can drive your own blendshape or morph target data in sync with audio playback. See Appendix F for more details. The opt object can be used to set text-specific lipsyncLang or skip all breaks and eye contacts by setting isRaw to true. streamStart(opt={}, onAudioStart = null, onAudioEnd = null, onSubtitles = null, onMetrics = null) | Sets the talking head in streaming mode. See Appendix G for streaming instructions. streamAudio(audio) | Starts feeding audio chunks to talkinghead in the streaming mode. See Appendix G for streaming instructions. streamNotifyEnd() | Signals the end of streaming audio chunks to the talkinghead. See Appendix G for streaming instructions. streamInterrupt() | Interrupts ongoing audio and lip-sync in streaming mode without ending the session. See Appendix G for streaming instructions. streamStop() | Exits the streaming mode and ends the session. See Appendix G for streaming instructions. speakEmoji(e) | Add an emoji e to the speech queue. speakBreak(t) | Add a break of t milliseconds to the speech queue. speakMarker(onmarker) | Add a marker to the speech queue. The callback function onmarker is called when the queue processes the marker. lookAt(x,y,t) | Make the avatar's head turn to look at the screen position (x,y) for t milliseconds. lookAhead(t) | Make avatar look ahead for t milliseconds. lookAtCamera(t) | Make the avatar's head turn to look at the camera for t milliseconds. If avatarIgnoreCamera is set to true, looks ahead for t milliseconds. makeEyeContact(t) | Make the avatar maintain eye contact with the person in front of it for (at least) t milliseconds. setMood(mood) | Set avatar mood. playBackgroundAudio(url) | Play background audio such as ambient sounds/music in a loop. stopBackgroundAudio() | Stop playing the background audio. setMixerGain(speech, [background=null], [fadeSecs=0]) | The amount of gain for speech and background audio (see Web Audio API / GainNode for more information). Value null means no change. Optional fadeSecs parameter sets exponential fade in/out time in seconds. playAnimation(url, [onprogress=null], [dur=10], [ndx=0], [scale=0.01]) | Play Mixamo animation file for dur seconds, but full rounds and at least once. If the FBX file includes several animations, the parameter ndx specifies the index. Since Mixamo rigs have a scale 100 and RPM a scale 1, the scale factor can be used to scale the positions. stopAnimation() | Stop the current animation started by playAnimation. playPose(url, [onprogress=null], [dur=5], [ndx=0], [scale=0.01]) | Play the initial pose of a Mixamo animation file for dur seconds. If the FBX file includes several animations, the parameter ndx specifies the index. Since Mixamo rigs have a scale 100 and RPM a scale 1, the scale factor can be used to scale the positions. stopPose() | Stop the current pose started by playPose. playGesture(name, [dur=3], [mirror=false], [ms=1000]) | Play a named hand gesture and/or animated emoji for dur seconds with the ms transition time. The available hand gestures are handup, index, ok, thumbup, thumbdown, side, shrug. By default, hand gestures are done with the left hand. If you want the right handed version, set mirror to true. You can also use playGesture to play emojis. See Appendix D for more details. stopGesture([ms=1000]) | Stop the gesture with ms transition time. startListening(analyzer, [opt={}], [onchange=null]) | Start listening analyzer AnalyserNode. The opt object can be used to set options listeningSilenceThresholdLevel, listeningSilenceThresholdMs, listeningSilenceDurationMax, listeningActiveThresholdLevel, listeningActiveThresholdMs, listeningActiveDurationMax. The callback function onchange is called, when the state changes with one of the following parameter: start, stop, maxsilence, maxactive. stopListening | Stop listening the incoming audio. start | Start/re-start the Talking Head animation loop. stop | Stop the Talking Head animation loop.

The class has been tested on the latest Chrome, Firefox, Safari, and Edge desktop browsers, as well as on iPad.

The index.html Test App

NOTE: The index.html app was created for testing and developing the TalkingHead class. It includes various integrations with several paid services. If you only want to use the TalkingHead class in your own app, there is no need to install and configure the index.html app.

In addition to testing and development, the test app be used as an example of how to integrate the TalkingHead class with ElevenLabs WebSocket API, Microsoft Azure Speech SDK, OpenAI, Gemini and Grok.

You can try out the test app online here on GitHub. By default, the text-to-speech and AI features will not work, but you can activate them by navigating to the settings menu (☰) and pasting your own API key in the relevant field(s). Your API keys will not be stored, so you will need to re-enter them each time you reload the page.

To set up the test app in your local environment, follow these steps:

1. Copy the latest files to your own web server, for example:

git clone --depth 1 https://github.com/met4citizen/TalkingHead.git && rm -r TalkingHead/.git

2. Optional: Create API proxies as described in Appendix B and check/update your proxy configuration in index.html:

// API proxys
const jwtEndpoint = "/app/jwt/get"; // Get JSON Web Token for Single Sign-On
const openaiChatCompletionsProxy = "/openai/v1/chat/completions";
const openaiModerationsProxy = "/openai/v1/moderations";
const openaiAudioTranscriptionsProxy = "/openai/v1/audio/transcriptions";
const vertexaiChatCompletionsProxy = "/vertexai/";
const googleTTSProxy = "/gtts/";
const elevenTTSProxy = [
  "wss://" + window.location.host + "/elevenlabs/",
  "/v1/text-to-speech/",
  "/stream-input?model_id=eleven_multilingual_v2&output_format=pcm_22050"
];
const microsoftTTSProxy = [
  "wss://" + window.location.host + "/mstts/",
  "/cognitiveservices/websocket/v1"
];
const grokChatCompletionsProxy = "/grok/v1/chat/completions"; // Grok-beta
const llamaChatCompletionsProxy = "/llama/v1/chat/completions"; // Local llama.cpp
const localWhisperCppProxy = "/whisper/"; // Local whisper.cpp

3. The test app's UI supports Finnish and English. If you want to add another language, you need to add an another entry to the i18n object.

4. Add you own background images, videos, audio files, avatars etc. in the directory structure and update your site configuration siteconfig.js accordingly. The keys are in English, but the entries can include translations to other languages.

Licenses, attributions and notes related to the index.html web app assets:

• The app uses Marked Markdown parser and DOMPurify XSS sanitizer.
• Fira Sans Condensed and Fira Sans Extra Condensed fonts are licensed under the SIL Open Font License, version 1.1, available with a FAQ at http://scripts.sil.org/OFL. Digitized data copyright (c) 2012-2015, The Mozilla Foundation and Telefonica S.A.
• SVG icons from css.gg, MIT License (versions prior to license update).
• Example avatar "brunette.glb" was created at Ready Player Me. The avatar is free to all developers for non-commercial use under the CC BY-NC 4.0 DEED. If you want to integrate Ready Player Me avatars into a commercial app or game, you must sign up as a Ready Player Me developer.
• Example animation walking.fbx and the pose dance.fbx are from Mixamo, a subsidiary of Adobe Inc. Mixamo service is free and its animations/poses (>2000) can be used royalty free for personal, commercial, and non-profit projects. Raw animation files can't be distributed outside the project team and can't be used to train ML models.
• Background view examples are from Virtual Backgrounds
• Impulse response (IR) files for reverb effects:
  • ir-room: OpenAir, Public Domain Creative Commons license
  • ir-basement: OpenAir, Public Domain Creative Commons license
  • ir-forest (Abies Grandis Forest, Wheldrake Wood): OpenAir, Creative Commons Attribution 4.0 International License
  • ir-church (St. Andrews Church): OpenAir, Share Alike Creative Commons 3.0
• Ambient sounds/music attributions:
  • murmur.mp3: https://github.com/siwalikm/coffitivity-offline

NOTE: None of the assets described above are used or distributed as part of the TalkingHead class releases. If you wish to use them in your own application, please refer to the exact terms of use provided by the copyright holders.

FAQ

Why not use the free Web Speech API?

The free Web Speech API can't provide word-to-audio timestamps, which are essential for accurate lip-sync. As far as I know, there is no way even to get Web Speech API speech synthesis as an audio file or determine its duration in advance. At some point I tried to use the Web Speech API events for syncronization, but the results were not good.

What paid text-to-speech service should I use?

It depends on your use case and budget. If the built-in lip-sync support is sufficient for your needs, I would recommend Google TTS, because it gives you up to 4 million characters for free each month. If your app needs to support multiple languages, I would consider Microsoft Speech SDK.

I would like to have lip-sync support for language X.

You have two options. First, you can implement a word-to-viseme class similar to those that currently exist for English and Finnish. See Appendix C for detailed instructions. Alternatively, you can check if Microsoft Azure TTS can provide visemes for your language and use Microsoft Speech SDK integration (speakAudio) instead of Google TTS and the built-in lip-sync (speakText).

Can I use a custom 3D model?

The class supports full-body Ready Player Me avatars. You can also make your own custom model, but it needs to have a RPM compatible rig/bone structure and all their blend shapes. Please refer to Appendix A and readyplayer.me documentation for more details.

Any future plans for the project?

This is just a small side-project for me, so I don't have any big plans for it. That said, there are several companies that are currently developing text-to-3D-avatar and text-to-3D-animation features. If and when they get released as APIs, I will probably take a look at them and see if they can be used/integrated in some way to the project.

References

[1] Finnish pronunciation, Wiktionary

[2] Elovitz, H. S., Johnson, R. W., McHugh, A., Shore, J. E., Automatic Translation of English Text to Phonetics by Means of Letter-to-Sound Rules (NRL Report 7948). Naval Research Laboratory (NRL). Washington, D. C., 1976. https://apps.dtic.mil/sti/pdfs/ADA021929.pdf

Appendix A: Create Your Own 3D Avatar

FOR HOBBYISTS:

1. Create your own full-body avatar free at https://readyplayer.me/avatar/ or https://playerzero.readyplayer.me/.

2. Copy your avatar’s unique ID (e.g., 64bfa15f0e72c63d7c3934a6) and download the GLB file using one of the links below. Replace the ID with your own, and make sure to keep the URL parameters to include the necessary morph targets (blend shapes).Ready Player Me:https://models.readyplayer.me/64bfa15f0e72c63d7c3934a6.glb?morphTargets=ARKit,Oculus+Visemes,mouthOpen,mouthSmile,eyesClosed,eyesLookUp,eyesLookDown&textureSizeLimit=1024&textureFormat=pngPlayerZero:https://avatars.readyplayer.me/67ebd62a688cd661ebe09988.glb?morphTargetsGroup=ARKit,Oculus+Visemes&morphTargets=mouthSmile,mouthOpen,eyesClosed,eyesLookUp,eyesLookDown&textureSizeLimit=1024&textureFormat=pngDepending on your use case, you can customize the texture format and texture quality (e.g. textureFormat=webp&textureQuality=high), the triangle count (e.g. lod=1), use Draco mesh compression (useDracoMeshCompression=true), and so on. See the full list of option here.

FOR 3D MODELERS:

You can create and use your own 3D full-body model, but it has to be Ready Player Me compatible. Their rig has a Mixamo-compatible bone structure described here:

https://docs.readyplayer.me/ready-player-me/api-reference/avatars/full-body-avatars

For lip-sync and facial expressions, you also need to have ARKit and Oculus compatible blend shapes, and a few additional ones, all listed in the following two pages:

https://docs.readyplayer.me/ready-player-me/api-reference/avatars/morph-targets/apple-arkit https://docs.readyplayer.me/ready-player-me/api-reference/avatars/morph-targets/oculus-ovr-libsync

[!TIP]
The additional blend shapes mentioned in the specs ("mouthOpen", "mouthSmile", "eyesClosed", "eyesLookUp", "eyesLookDown") are not strictly required, as the TalkingHead class will automatically generate them from ARKit blend shapes if they are missing.

The TalkingHead class supports both separated mesh and texture atlasing.

Here are some Blender Python scripts that could be useful in converting custom models:

Script | Description --- | --- rename-mixamo-bones.py | If your model doesn't have a compatible rig, you can auto-rig your model easily at Mixamo and use this Blender script to rename the Mixamo bones. rename-rocketbox-shapekeys.py | Rename Microsoft Rocketbox model shape keys. rename-avatarsdk-shapekeys.py | Rename Avatar SDK MetaPerson model shape keys. build-extras-from-arkit.py | Build RPM extras (mouthOpen, mouthSmile, eyesClosed, eyesLookUp, eyesLookDown) from ARKit blendshapes. Note: The TalkingHead will generate these automatically if they're missing. However, building them yourself allows you to fine-tune them to your taste. build-visemes-from-arkit.py | Build Oculus visemes from ARKit blendshapes. As models are all different, you should fine-tune the script for best result. EXPERIMENTAL

Appendix B: Create API Proxies with JSON Web Token (JWT) Single Sign-On (SSO)

1. Make a CGI script that generates a new JSON Web Token with an expiration time (exp). See jwt.io for more information about JWT and libraries that best fit your needs and architecture. In my own test setup, I return the generated JWT as JSON.

{ "jwt": "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzdWIiOiIxMjM0NTY3ODkwIiwibmFtZSI6IkpvaG4gRG9lIiwiaWF0IjoxNTE2MjM5MDIyfQ.SflKxwRJSMeKKF2QT4fwpMeJf36POk6yJV_adQssw5c" }

2. Protect your CGI script with some authentication scheme. Below is an example Apache 2.4 directory config that uses Basic authentication (remember to always use HTTPS/SSL!). Put your CGI script get in the jwt directory.

# Restricted applications
<Directory "/var/www/app">
  AuthType Basic
  AuthName "Restricted apps"
  AuthUserFile /etc/httpd/.htpasswd
  Require valid-user
</Directory>

# JSON Web Token
<Directory "/var/www/app/jwt" >
  Options ExecCGI
  SetEnv REMOTE_USER %{REMOTE_USER}
  SetHandler cgi-script
</Directory>

3. Make an External Rewriting Program script that verifies JSON Web Tokens. The script should return OK if the given token is not expired and its signature is valid. Start the script in Apache 2.4 config. User's don't use the verifier script directly, so put it in some internal directory, not under document root.

# JSON Web Token verifier
RewriteEngine On
RewriteMap jwtverify "prg:/etc/httpd/jwtverify" apache:apache

4. Make a proxy configuration for each service you want to use. Add the required API keys and protect the proxies with the JWT token verifier. Below are some example configs for Apache 2.4 web server. Note that when opening a WebSocket connection (ElevenLabs, Azure) you can't add authentication headers in browser JavaScript. This problem is solved here by including the JWT token as a part of the request URL. The downside is that the token might end up in server log files. This is typically not a problem as long as you are controlling the proxy server, you are using HTTPS/SSL, and the token has an expiration time.

# OpenAI API
<Location /openai/>
  RewriteCond ${jwtverify:%{http:Authorization}} !=OK
  RewriteRule .+ - [F]
  ProxyPass https://api.openai.com/
  ProxyPassReverse  https://api.openai.com/
  ProxyPassReverseCookiePath "/"  "/openai/"
  ProxyPassReverseCookieDomain ".api.openai.com" ".<insert-your-proxy-domain-here>"
  RequestHeader set Authorization "Bearer <insert-your-openai-api-key-here>"
</Location>

# Google TTS API
<Location /gtts/>
  RewriteCond ${jwtverify:%{http:Authorization}} !=OK
  RewriteRule .+ - [F]
  ProxyPass https://eu-texttospeech.googleapis.com/v1beta1/text:synthesize?key=<insert-your-api-key-here> nocanon
  RequestHeader unset Authorization
</Location>

# Microsoft Azure TTS WebSocket API (Speech SDK)
<LocationMatch /mstts/(?<jwt>[^/]+)/>
  RewriteCond ${jwtverify:%{env:MATCH_JWT}} !=OK
  RewriteRule .+ - [F]
  RewriteCond %{HTTP:Connection} Upgrade [NC]
  RewriteCond %{HTTP:Upgrade} websocket [NC]
  RewriteRule /mstts/[^/]+/(.+) "wss://<insert-your-region-here>.tts.speech.microsoft.com/$1" [P]
  RequestHeader set "Ocp-Apim-Subscription-Key" <insert-your-subscription-key-here>
</LocationMatch>

# ElevenLabs Text-to-speech WebSocket API
<LocationMatch /elevenlabs/(?<jwt>[^/]+)/>
  RewriteCond ${jwtverify:%{env:MATCH_JWT}} !=OK
  RewriteRule .+ - [F]
  RewriteCond %{HTTP:Connection} Upgrade [NC]
  RewriteCond %{HTTP:Upgrade} websocket [NC]
  RewriteRule /elevenlabs/[^/]+/(.+) "wss://api.elevenlabs.io/$1" [P]
  RequestHeader set "xi-api-key" "<add-your-elevenlabs-api-key-here>"
</LocationMatch>

Appendix C: Create A New Lip-sync Module

The steps that are common to all new languages:

• Create a new file named lipsync-xx.mjs where xx is your language code, and place the file in the ./modules/ directory. The language module should have a class named LipsyncXx where Xx is the language code. The naming in important, because the modules are loaded dynamically based on their names.
• The class should have (at least) the following two methods: preProcessText and wordsToVisemes. These are the methods used in the TalkingHead class.
• The purpose of the preProcessText method is to preprocess the given text by converting symbols to words, numbers to words, and filtering out characters that should be left unspoken (if any), etc. This is often needed to prevent ambiguities between TTS and lip-sync engines. This method takes a string as a parameter and returns the preprocessed string.
• The purpose of the wordsToVisemes method is to convert the given text into visemes and timestamps. The method takes a string as a parameter and returns a lip-sync object. The lipsync object has three required properties: visemes, timesand durations.
  • Property visemes is an array of Oculus OVR viseme codes. Each viseme is one of the strings: 'aa', 'E', 'I', 'O', 'U', 'PP', 'SS', 'TH', 'CH', 'FF', 'kk', 'nn', 'RR', 'DD', 'sil'. See the reference images here: https://developer.oculus.com/documentation/unity/audio-ovrlipsync-viseme-reference/
  • Property times is an array of starting times, one entry for each viseme in visemes. Starting times are to be given in relative units. They will be scaled later on based on the word timestamps that we get from the TTS engine.
  • Property durations is an array of relative durations, one entry for each viseme in visemes. Durations are to be given in relative units. They will be scaled later on based on the word timestamps that we get from the TTS engine.

The difficult part is to actually make the conversion from words to visemes. What is the best approach depends on the language. Here are some typical approaches to consider (not a comprehensive list):

• Direct mapping from graphemes to phonemes to visemes. This works well for languages that have a consistent one-to-one mapping between individual letters and phonemes. This was used as the approach for the Finnish language (lipsync-fi.mjs) giving >99.9% lip-sync accuracy compared to the Finnish phoneme dictionary. Implementation size was ~4k. Unfortunately not all languages are phonetically orthographic languages.
• Rule-based mapping. This was used as the approach for the English language (lipsync-en.mjs) giving around 80% lip-sync accuracy compared to the English phoneme dictionary. However, since the rules cover the most common words, the effective accuracy is higher. Implementation size ~12k.
• Dictionary based approach. If neither of the previous approaches work for your language, make a search from some open source phoneme dictionary. Note that you still need some backup algorithm for those words that are not in the dictionary. The problem with phoneme dictionaries is their size. For example, the CMU phoneme dictionary for English is ~5M.
• Neural-net approach based on transformer models. Typically this should be done on server-side as the model size can be >50M.

TalkingHead is supposed to be a real-time class, so latency is always something to consider. It is often better to be small and fast than to aim for 100% accuracy.

Appendix D: Adding Custom Poses, Moods, Gestures, and Emojis (ADVANCED)

In the TalkingHead class, the avatar's movements are based on four data structures: head.poseTemplates, head.animMoods, head.gestureTemplates, and head.animEmojis. By using these objects, you can give your avatar its own personal body language.

In head.poseTemplates the hip position is defined as an {x, y, z} coordinate in meters, and bone rotations as Euler XYZ rotations in radians. In each pose, the avatar should have its weight on the left leg, if any, as the class automatically mirrors it for the right side. Setting the boolean properties standing, sitting, bend, kneeling, and lying helps the class make the transitions between different poses in proper steps.

head.poseTemplates["custom-pose-1"] = {
  standing: true, sitting: false, bend: false, kneeling: false, lying: false,
  props: {
    'Hips.position':{x:0, y:0.989, z:0.001}, 'Hips.rotation':{x:0.047, y:0.007, z:-0.007}, 'Spine.rotation':{x:-0.143, y:-0.007, z:0.005}, 'Spine1.rotation':{x:-0.043, y:-0.014, z:0.012}, 'Spine2.rotation':{x:0.072, y:-0.013, z:0.013}, 'Neck.rotation':{x:0.048, y:-0.003, z:0.012}, 'Head.rotation':{x:0.05, y:-0.02, z:-0.017}, 'LeftShoulder.rotation':{x:1.62, y:-0.166, z:-1.605}, 'LeftArm.rotation':{x:1.275, y:0.544, z:-0.092}, 'LeftForeArm.rotation':{x:0, y:0, z:0.302}, 'LeftHand.rotation':{x:-0.225, y:-0.154, z:0.11}, 'LeftHandThumb1.rotation':{x:0.435, y:-0.044, z:0.457}, 'LeftHandThumb2.rotation':{x:-0.028, y:0.002, z:-0.246}, 'LeftHandThumb3.rotation':{x:-0.236, y:-0.025, z:0.113}, 'LeftHandIndex1.rotation':{x:0.218, y:0.008, z:-0.081}, 'LeftHandIndex2.rotation':{x:0.165, y:-0.001, z:-0.017}, 'LeftHandIndex3.rotation':{x:0.165, y:-0.001, z:-0.017}, 'LeftHandMiddle1.rotation':{x:0.235, y:-0.011, z:-0.065}, 'LeftHandMiddle2.rotation':{x:0.182, y:-0.002, z:-0.019}, 'LeftHandMiddle3.rotation':{x:0.182, y:-0.002, z:-0.019}, 'LeftHandRing1.rotation':{x:0.316, y:-0.017, z:0.008}, 'LeftHandRing2.rotation':{x:0.253, y:-0.003, z:-0.026}, 'LeftHandRing3.rotation':{x:0.255, y:-0.003, z:-0.026}, 'LeftHandPinky1.rotation':{x:0.336, y:-0.062, z:0.088}, 'LeftHandPinky2.rotation':{x:0.276, y:-0.004, z:-0.028}, 'LeftHandPinky3.rotation':{x:0.276, y:-0.004, z:-0.028}, 'RightShoulder.rotation':{x:1.615, y:0.064, z:1.53}, 'RightArm.rotation':{x:1.313, y:-0.424, z:0.131}, 'RightForeArm.rotation':{x:0, y:0, z:-0.317}, 'RightHand.rotation':{x:-0.158, y:-0.639, z:-0.196}, 'RightHandThumb1.rotation':{x:0.44, y:0.048, z:-0.549}, 'RightHandThumb2.rotation':{x:-0.056, y:-0.008, z:0.274}, 'RightHandThumb3.rotation':{x:-0.258, y:0.031, z:-0.095}, 'RightHandIndex1.rotation':{x:0.169, y:-0.011, z:0.105}, 'RightHandIndex2.rotation':{x:0.134, y:0.001, z:0.011}, 'RightHandIndex3.rotation':{x:0.134, y:0.001, z:0.011}, 'RightHandMiddle1.rotation':{x:0.288, y:0.014, z:0.092}, 'RightHandMiddle2.rotation':{x:0.248, y:0.003, z:0.02}, 'RightHandMiddle3.rotation':{x:0.249, y:0.003, z:0.02}, 'RightHandRing1.rotation':{x:0.369, y:0.019, z:0.006}, 'RightHandRing2.rotation':{x:0.321, y:0.004, z:0.026}, 'RightHandRing3.rotation':{x:0.323, y:0.004, z:0.026}, 'RightHandPinky1.rotation':{x:0.468, y:0.085, z:-0.03}, 'RightHandPinky2.rotation':{x:0.427, y:0.007, z:0.034}, 'RightHandPinky3.rotation':{x:0.142, y:0.001, z:0.012}, 'LeftUpLeg.rotation':{x:-0.077, y:-0.058, z:3.126}, 'LeftLeg.rotation':{x:-0.252, y:0.001, z:-0.018}, 'LeftFoot.rotation':{x:1.315, y:-0.064, z:0.315}, 'LeftToeBase.rotation':{x:0.577, y:-0.07, z:-0.009}, 'RightUpLeg.rotation':{x:-0.083, y:-0.032, z:3.124}, 'RightLeg.rotation':{x:-0.272, y:-0.003, z:0.021}, 'RightFoot.rotation':{x:1.342, y:0.076, z:-0.222}, 'RightToeBase.rotation':{x:0.44, y:0.069, z:0.016}
  }
};
head.playPose("custom-pose-1");

In head.animMoods the syntax is more complex, so I suggest that you take a look at the existing moods. In anims, each leaf object is an animation loop template. Whenever a loop starts, the class iterates through the nested hierarchy of objects by following keys that match the current state (idle, talking), body form (M, F), current view (full, upper, mid, head), and/or probabilities (alt + p). The next animation will be created internally by using the animFactory method. The property delay (ms) determines how long that pose is held, dt defines durations (ms) for each part in the sequence, and vs defines the shapekeys and their target values for each part.

head.animMoods["custom-mood-1"] = {
  baseline: { eyesLookDown: 0.1 },
  speech: { deltaRate: 0, deltaPitch: 0, deltaVolume: 0 },
  anims: [
    { name: 'breathing', delay: 1500, dt: [ 1200,500,1000 ], vs: { chestInhale: [0.5,0.5,0] } },
    { name: 'pose', alt: [
      { p: 0.2, delay: [5000,20000], vs: { pose: ['side'] } },
      { p: 0.2, delay: [5000,20000], vs: { pose: ['hip'] },
        'M': { delay: [5000,20000], vs: { pose: ['wide'] } }
      },
      { delay: [5000,20000], vs: { pose: ['custom-pose-1'] } }
    ]},
    { name: 'head',
      idle: { delay: [0,1000], dt: [ [200,5000] ], vs: { headRotateX: [[-0.04,0.10]], headRotateY: [[-0.3,0.3]], headRotateZ: [[-0.08,0.08]] } },
      talking: { dt: [ [0,1000,0] ], vs: { headRotateX: [[-0.05,0.15,1,2]], headRotateY: [[-0.1,0.1]], headRotateZ: [[-0.1,0.1]] } }
    },
    { name: 'eyes', delay: [200,5000], dt: [ [100,500],[100,5000,2] ], vs: { eyesRotateY: [[-0.6,0.6]], eyesRotateX: [[-0.2,0.6]] } },
    { name: 'blink', delay: [1000,8000,1,2], dt: [50,[100,300],100], vs: { eyeBlinkLeft: [1,1,0], eyeBlinkRight: [1,1,0] } },
    { name: 'mouth', delay: [1000,5000], dt: [ [100,500],[100,5000,2] ], vs : { mouthRollLower: [[0,0.3,2]], mouthRollUpper: [[0,0.3,2]], mouthStretchLeft: [[0,0.3]], mouthStretchRight: [[0,0.3]], mouthPucker: [[0,0.3]] } },
    { name: 'misc', delay: [100,5000], dt: [ [100,500],[100,5000,2] ], vs : { eyeSquintLeft: [[0,0.3,3]], eyeSquintRight: [[0,0.3,3]], browInnerUp: [[0,0.3]], browOuterUpLeft: [[0,0.3]], browOuterUpRight: [[0,0.3]] } }
  ]
};
head.setMood("custom-mood-1");

Typical value range is [0,1] or [-1,1]. At the end of each animation, the value will automatically return to its baseline value. If the value is an array, it defines a range for a uniform/Gaussian random value (approximated using CLT). See the class method gaussianRandom for more information.

In head.gestureTemplates each property is a subset of bone rotations that will be used to override the current pose.

head.gestureTemplates["salute"] = {
  'LeftShoulder.rotation':{x:1.706, y:-0.171, z:-1.756}, 'LeftArm.rotation':{x:0.883, y:-0.288, z:0.886}, 'LeftForeArm.rotation':{x:0, y:0, z:2.183}, 'LeftHand.rotation':{x:0.029, y:-0.298, z:0.346}, 'LeftHandThumb1.rotation':{x:1.43, y:-0.887, z:0.956}, 'LeftHandThumb2.rotation':{x:-0.406, y:0.243, z:0.094}, 'LeftHandThumb3.rotation':{x:-0.024, y:0.008, z:-0.012}, 'LeftHandIndex1.rotation':{x:0.247, y:-0.011, z:-0.084}, 'LeftHandIndex2.rotation':{x:0.006, y:0, z:0}, 'LeftHandIndex3.rotation':{x:-0.047, y:0, z:0.004}, 'LeftHandMiddle1.rotation':{x:0.114, y:-0.004, z:-0.055}, 'LeftHandMiddle2.rotation':{x:0.09, y:0, z:-0.007}, 'LeftHandMiddle3.rotation':{x:0.078, y:0, z:-0.006}, 'LeftHandRing1.rotation':{x:0.205, y:-0.009, z:0.023}, 'LeftHandRing2.rotation':{x:0.109, y:0, z:-0.009}, 'LeftHandRing3.rotation':{x:-0.015, y:0, z:0.001}, 'LeftHandPinky1.rotation':{x:0.267, y:-0.012, z:0.031}, 'LeftHandPinky2.rotation':{x:0.063, y:0, z:-0.005}, 'LeftHandPinky3.rotation':{x:0.178, y:-0.001, z:-0.014}
};
head.playGesture("salute",3);

In head.animEmojis each object is an animated emoji. Note that you can also use head.playGesture to play animated emojis. This makes it easy to combine a hand gesture and a facial expression by giving the gesture and the emoji the same name.

head.animEmojis["🫤"] = { dt: [300,2000], vs: {
    browInnerUp: [0.5], eyeWideLeft: [0.5], eyeWideRight: [0.5], mouthLeft: [0.5], mouthPressLeft: [0.8], mouthPressRight: [0.2], mouthRollLower: [0.5], mouthStretchLeft: [0.7],   mouthStretchRight: [0.7]
  }
};
head.playGesture("🫤",3);

Appendix E: Dynamic Bones (ADVANCED)

If you want your character's hair or other body parts to wiggle as the character moves, you can use TalkingHead's Dynamic Bones feature. The built-in physics engine simulates Newton's equations of motions using a spring-damper model and the velocity Verlet integration method.

Standard Ready Player Me 3D avatars don't yet include features like hair bones. Until they do, you'll need to add the dynamic bones and weights to the model yourself. Here's an example of rigged hair in Blender.

Once your custom rig is in place, you can configure the dynamic bones by setting the modelDynamicBones property to the avatar object of the showAvatar method. Here's an example:

// Load and show the avatar
try {
  await head.showAvatar( {
    url: './avatars/custom.glb',
    body: 'F',
    avatarMood: 'neutral',
    ttsLang: "en-GB",
    ttsVoice: "en-GB-Standard-A",
    lipsyncLang: 'en',
    modelDynamicBones: [
      {
        bone: "ponytail1", type: "full", stiffness: 20, damping: 2,
        limits: [null,null,[null,0.01],null],
      },
      {
        bone: "ponytail2", type: "full", stiffness: 200, damping: 10,
        pivot: true
      },
      {
        bone: "ponytail3", type: "full", stiffness: 400, damping: 10,
        excludes: [{"bone":"Head","deltaLocal":[0,0.05,0.02],"radius":0.13}]
      }
    ]
  });
} catch (error) {
  console.log(error);
}

Each item in modelDynamicBones array represents one dynamic bone, which can be configured separately.

Property | Description | Example --- | --- | --- bone | The name of the bone in your custom skeleton. Note that each dynamic bone must have a parent bone. | "ponytail1" type | "point" updates only the bone's local position [x,y,z]. It is fast to calculate, but may cause skinned meshes to deform unnaturally."link" updates only the parent's quaternions (XZ rotations)."mix1" mixes XZ rotations with a stretch (bone length, position change)."mix2" mixes XZ rotations with a twist (Y rotations)."full" link with both stretch and twist. | "full" stiffness | Mass-normalized spring constant k [m/s^2]. Either a non-negative number or an array with separate values for each dimension [x, y, z, t]. | 20 damping | Mass-normalized damping coefficient c [1/s]. Either a non-negative number or an array with separate values for each dimension [x, y, z, t]. | 2 external | External scaling factor between [0,1] that can be used to scale down the external forces caused by parent's movement. If set to 0, the bone is rigid and moves with its parent without experiencing any external force. If set to 1, the bone follows its parent with a lag (inertia) and feels the force. OPTIONAL, default value 1.0 | 0.7 limits | Sets the limiting range [low, high] for each dimension [x, y, z, t] in meters [m]. This can help prevent situations in which meshes overlap due to sudden movements or when the amplitude becomes unrealistic. Limits are applied in local space. OPTIONAL, default null (no limit) | [null,null,[null,0.01],null] deltaLocal | Local position translation [dx,dy,dz] in meters [m]. OPTIONAL, default null | [0,0.01,0] deltaWorld | World position translation [dx,dy,dz] in meters [m]. OPTIONAL, default null | [0,-0.02,0] pivot | If true, the bone becomes a free-hanging bone along the Y-axis. This means that the parent's X/Z rotations are automatically compensated. Use with caution, as this requires additional computational effort, and the limits do not apply as usual. OPTIONAL, default false | true excludes | Sets one or more spherical excluded zones that act as invisible force fields, limiting the movement of the bone. An array of objects in the format { bone, deltaLocal, radius} in which bone specifies the center bone name, deltaLocal (optional) offset [x,y,z] relative to center bone, and radius in meters. OPTIONAL, default null | [ { bone: "Head", deltaLocal: [0,0.05,0.02], radius: 0.13 } ] helper | If true, add a helper object to the scene to assist with visualizing the bone during testing. If the dynamic bone type is "point", displays only a square, otherwise also the line from parent to the bone. OPTIONAL, default false | true

Finding a good combination of stiffness, damping, and external, is mostly a matter of trial and error. Turn on the helper property or use the test app to fine-tune the settings while running animations typical to your use case.

[!TIP] For dynamic bones of type "point", you can simulate gravity by applying a deltaWorld translation down the Y-axis and compensating for the initial stretch in the rest pose by applying deltaLocal translation up the Y-axis.

Appendix F: Controlling Blendshapes Directly (Advanced)

The TalkingHead class provides basic facial expressions and animations by controlling the 3D avatar's blendshapes (a.k.a. morph targets). It also possible to control these blendshapes directly from your app. Below are some of the available approaches, with simple code examples:

• Use setFixedValue method to smoothly transition from the current blendshape value to some fixed value. The fixed value will override all other methods as well as internal/external animations. To return back to normal operation, set the fixed value to null:

head.setFixedValue("jawOpen",1);

• Use the realtime value of the head.mtAvatar property to set the blend shape value without any smooth transition. This is useful for cases like face landmark detection, where you need to stay in sync with real-time input. To return back to normal operation, set the realtime value to null:

Object.assign( head.mtAvatar["jawOpen"],{ realtime: 1, needsUpdate: true });

• Add an animation template object anim to the audio data in speakAudio to drive blendshapes in sync with audio playback. This is especially useful when using facial animation data from external sources (e.g., Azure TTS 3D blendshapes or motion capture) and want to play it alongside spoken audio:

head.speakAudio({
  audio: audio,
  anim: {
    name: "blendshapes",
    dt: [ 33, 33, 33, ... ],  // durations in milliseconds for each frame
    vs: { // Blend shape keys and values for each frame
      "jawOpen": [ 0, 0.2, 0.4, ... ],
      "mouthRollLower": [ 0, 0.05, 0.1, ... ],
      // ... additional blendshape keys
    }
  }
});

See a full code example using Azure blendshape output here. - Note: Azure's output relies solely on ARKit blendshapes and is not optimized for RPM avatars. As a result, the quality of lip-sync may be less natural compared to using Oculus visemes and the TalkingHead's internal lip-sync language module. For example, the mouth may open too widely, or the lips may fail to touch for certain phonemes they should.

See also the next Appendix G for how to stream audio with lip-sync.

Appendix G: Streaming Audio and Lip-sync (Advanced)

This low-level streaming interface is designed for real-time scenarios, such as speech-to-speech or live TTS integrations where latency must be minimized. Use this interface if you require direct, chunked audio playback and on-the-fly lip-sync updates. You can, for instance, integrate a real-time TTS pipeline (like Azure Speech SDK or another live audio source) that continuously streams audio and word/viseme data into TalkingHead.

Important: The calling application must handle all aspects of managing and synchronizing the data streams (e.g., facial expressions, eye contact, hand gestures), as well as preventing concurrency issues and buffering multiple sources. The system is designed to handle one stream at a time.

Stream Session Reusability

Once a streaming session is started with streamStart(), the session remains active and reusable until explicitly ended with streamStop(). You can:

• Natural completion: Call streamNotifyEnd() after streaming all data with streamAudio() to signal the end of an utterance. The session remains active for reuse.
• Interruption: Call streamInterrupt() to immediately stop ongoing audio and lip-sync. The session remains active for reuse.
• Reconfiguration: Call streamStart() again at any time to reconfigure the session with new options.
• Session termination: Call streamStop() to completely end the streaming session.

API Overview

1. streamStart(opt={}, onAudioStart, onAudioEnd, onSubtitles, onMetrics)

Enters streaming mode using an AudioWorklet for low-latency playback. Parameters:

• opt (object, optional) – Settings controlling streaming behavior:
  • sampleRate – A number in the range [8000, 96000].
  • gain – Sets the playback gain (volume) for the streaming audio.
  • lipsyncLang – Specifies lip-sync language if you want viseme generation using words. Defaults to avatar lipsyncLang, or to options lipsyncLang value.
  • lipsyncType – Specifies lip-sync data type. Can take one of the values visemes (default), blendshapes, and words.
  • waitForAudioChunks – Boolean (default: true). If false, lip-sync will play immediately without waiting for audio chunks. This can be used to play lip-sync without audio.
  • mood – Sets avatar mood upon starting the stream.
  • metrics – Used for in development performance monitoring: {enabled: true, intervalHz: 2}. Enables queue depth and underrun tracking in the audio worklet. Do not set in production.
• onAudioStart (function, optional) – Callback invoked the moment audio playback starts.
• onAudioEnd (function, optional) – Callback invoked automatically once audio playback concludes.
• onSubtitles (function, optional) – Callback to handle showing subtitle text.
• onMetrics (function, optional) – Callback receiving performance monitoring data: queue depth, underruns, playback state.

Upon calling streamStart, all queued speech (speakText, speakAudio) is stopped, the engine enters streaming mode, and the avatar prepares for real-time lip-sync. You can then feed audio via streamAudio(). The session remains active until streamStop() is called.

2. streamAudio(r)

Sends one chunk of PCM audio data (16-bit little-endian) plus lip-sync data. Parameters:

• r.audio – An ArrayBuffer or typed array of 16-bit LE PCM samples. These are played immediately.
• r.visemes, r.vtimes, r.vdurations (optional) – Directly schedule lip-sync visemes at specific times with specific durations. This is the default type of lip-sync data.
• r.words, r.wtimes, r.wdurations (optional) – Per-word timings and durations (e.g. TTS), allowing the library to create subtitles and/or calculate visemes if the lipsyncType option is set to words.
• r.anims (optional) – An array of blendshape animations that play in sync with the audio. Requires setting lipsyncType option to blendshapes.

Each call to streamAudio() schedules an immediate chunk for playback and any included lip-sync or subtitle data on the animation timeline. Include only lip-sync data as specified in the lipsyncType option via the streamStart call. You can include any number of visemes, anims, or words which are not necessarily associated with the included audio chunk. You need to buffer the lip-sync data in the application and send it alongside the audio chunks.

3. streamNotifyEnd()

Signals that no more chunks are expected for the current streaming utterance. Playback stops automatically once queued audio finishes. This is useful for gracefully concluding real-time TTS streams when your pipeline has no additional data to send. The streaming session remains active and can be reused by calling streamAudio() again. After the call, wait untill the playback has ended to have effect. If streamAudio() is called after streamNotifyEnd() and before the playback has ended, the notification end is canceled.

4. streamInterrupt()

Immediately interrupts any ongoing audio playback and lip-sync animations in the streaming session. This method stops the current utterance but keeps the streaming session active for reuse. You can continue using the session by calling streamAudio() again after interruption.

5. streamStop()

Forces an immediate end to the streaming session. All queued audio and lip-sync animations are cleared, the avatar reverts to its idle state, and the audio worklet is disconnected and cleaned up. To start streaming again after calling streamStop(), you must call streamStart() to create a new session.

Example Usage

Refer to the example provided in the repository azure-audio-streaming.html on how to integrate this interface with Azure TTS streamed audio.

Appendix H: Avatar-Only Mode (EXPERIMENTAL)

[!WARNING] This is still an experimental feature, so expect rapid changes.

By default, the TalkingHead class operates in standalone mode, creating its own 3D scene, renderer, lights, and other 3D components. If you already have your own 3D scene, you can create an avatar-only instance and call the head.animate(dt) update function from within your own renderer. For example:

// Create avatarOnly instance and load
const head = new TalkingHead( container, {
  /* ... */
  avatarOnly: true, // set avatarOnly mode
  avatarOnlyCamera: camera // Your camera avatar talks to
});
await head.showAvatar({ /* ... */ });

// Add to your own scene
head.armature.position.set(1,0,0);
head.armature.rotation.set(0,0.5,0);
scene.add(head.armature);

// You own animation loop
const clock = new THREE.Clock();
function animate() {
  const delta = clock.getDelta();
  head.animate(delta * 1000); // Update avatar
  renderer.render( scene, camera );
}
renderer.setAnimationLoop(animate);

You can also add avatarOnly armatures to your standalone TalkingHead scene to have multiple avatars in one scene. For example:

let headStandalone, headAvatarOnly;

// Standalone instance
headStandalone = new TalkingHead( container, {
  /* ... */
  update: (dt) => { headAvatarOnly?.animate(dt); }
});
await headStandalone.showAvatar({ /* ... */ });

// avatarOnly instance
headAvatarOnly = new TalkingHead( container, {
  /* ... */
  avatarOnly: true, // set avatarOnly mode
  avatarOnlyCamera: headStandalone.camera // Standalone camera
});
await headAvatarOnly.showAvatar({ /* ... */ });

// Add avatarOnly to standalone scene
headAvatarOnly.armature.position.set(1,0,0);
headStandalone.scene.add( headAvatarOnly.armature );

If you want one TalkingHead avatar to speak to another, set its speakTo property. The value can be another TalkingHead instance, any 3D object, or a world position. For example, to make two avatars talk to each other:

headAvatarOnly.speakTo = headStandalone;
headStandalone.speakTo = headAvatarOnly;

If you want the avatar to address the user again, set speakTo value to null.