All the demo videos are real-time screen captures from a Chrome browser running the TalkingHead test web app without any post-processing.
Video/App | Use Case |
---|---|
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 👍 | |
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 👏👏 | |
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 👋 |
Talking Head (3D) is a JavaScript class featuring a 3D avatar that can speak and lip-sync in real-time. The class supports Ready Player Me full-body 3D avatars (GLB), Mixamo animations (FBX), and subtitles. It also knows a set of emojis, which it can convert into facial expressions.
By default, the class uses Google Cloud TTS for text-to-speech and has a built-in lip-sync support for English, Finnish, and Lithuanian (beta). New lip-sync languages can be added by creating new lip-sync language modules. It is also possible to integrate the class with an external TTS service, such as Microsoft Azure Speech SDK or ElevenLabs WebSocket API.
The class uses ThreeJS / WebGL for 3D rendering.
You can download the TalkingHead modules from releases (without dependencies). Alternatively, you can import all the needed modules from a CDN:
<script type="importmap">
{ "imports":
{
"three": "https://cdn.jsdelivr.net/npm/three@0.170.0/build/three.module.js/+esm",
"three/addons/": "https://cdn.jsdelivr.net/npm/three@0.170.0/examples/jsm/",
"talkinghead": "https://cdn.jsdelivr.net/gh/met4citizen/TalkingHead@1.3/modules/talkinghead.mjs"
}
}
</script>
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"]
});
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.
The following table lists all the available options and their default values:
Option | Description |
---|---|
jwsGet |
Function to get the JSON Web Token (JWT). See Appendix B for more information. |
ttsEndpoint |
Text-to-speech backend/endpoint/proxy implementing the Google Text-to-Speech API. |
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. |
ttsLang |
Google text-to-speech language. Default is "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. Default voice is "fi-FI-Standard-A" . |
ttsRate |
Google text-to-speech rate in the range [0.25, 4.0]. Default is 1.0 . |
ttsPitch |
Google text-to-speech pitch in the range [-20.0, 20.0]. Default is 0 . |
ttsVolume |
Google text-to-speech volume gain (in dB) in the range [-96.0, 16.0]. Default is 0 . |
ttsTrimStart |
Trim the viseme sequence start relative to the beginning of the audio (shift in milliseconds). Default is 0 . |
ttsTrimEnd |
Trim the viseme sequence end relative to the end of the audio (shift in milliseconds). Default is 300 . |
mixerGainSpeech |
The amount of gain for speech. See Web Audio API / GainNode for more information. Default value is null (system default) [≥v1.3 ]. |
mixerGainBackground |
The amount of gain for background audio. See Web Audio API / GainNode for more information. Default value is null (system default) [≥v1.3 ]. |
lipsyncModules |
Lip-sync modules to load dynamically at start-up. Limiting the number of language modules improves the loading time and memory usage. Default is ["en", "fi", "lt"] . [≥v1.2 ] |
lipsyncLang |
Lip-sync language. Default is "fi" . |
pcmSampleRate |
PCM (signed 16bit little endian) sample rate used in speakAudio in Hz. Default is 22050 . |
modelRoot |
The root name of the armature. Default is Armature . |
modelPixelRatio |
Sets the device's pixel ratio. Default is 1 . |
modelFPS |
Frames per second. Note that actual frame rate will be a bit lower than the set value. Default is 30 . |
modelMovementFactor |
A factor in the range [0,1] limiting the avatar's upper body movement when standing. Default is 1 . [≥v1.2 ] |
cameraView |
Initial view. Supported views are "full" , "mid" , "upper" and "head" . Default is "full" . |
cameraDistance |
Camera distance offset for initial view in meters. Default is 0 . |
cameraX |
Camera position offset in X direction in meters. Default is 0 . |
cameraY |
Camera position offset in Y direction in meters. Default is 0 . |
cameraRotateX |
Camera rotation offset in X direction in radians. Default is 0 . |
cameraRotateY |
Camera rotation offset in Y direction in radians. Default is 0 . |
cameraRotateEnable |
If true, the user is allowed to rotate the 3D model. Default is true . |
cameraPanEnable |
If true, the user is allowed to pan the 3D model. Default is false . |
cameraZoomEnable |
If true, the user is allowed to zoom the 3D model. Default is false . |
lightAmbientColor |
Ambient light color. The value can be a hexadecimal color or CSS-style string. Default is 0xffffff . |
lightAmbientIntensity |
Ambient light intensity. Default is 2 . |
lightDirectColor |
Direction light color. The value can be a hexadecimal color or CSS-style string. Default is 0x8888aa . |
lightDirectIntensity |
Direction light intensity. Default is 30 . |
lightDirectPhi |
Direction light phi angle. Default is 0.1 . |
lightDirectTheta |
Direction light theta angle. Default is 2 . |
lightSpotColor |
Spot light color. The value can be a hexadecimal color or CSS-style string. Default is 0x3388ff . |
lightSpotIntensity |
Spot light intensity. Default is 0 . |
lightSpotPhi |
Spot light phi angle. Default is 0.1 . |
lightSpotTheta |
Spot light theta angle. Default is 4 . |
lightSpotDispersion |
Spot light dispersion. Default is 1 . |
avatarMood |
The mood of the avatar. Supported moods: "neutral" , "happy" , "angry" , "sad" , "fear" , "disgust" , "love" , "sleep" . Default is "neutral" . |
avatarMute |
Mute the avatar. This can be helpful option if you want to output subtitles without audio and lip-sync. Default is false . |
avatarIdleEyeContact |
The average proportion of eye contact while idle in the range [0,1]. Default is 0.2 . [≥v1.3 ] |
avatarIdleHeadMove |
The average proportion of head movement while idle in the range [0,1]. Default is 0.5 . [≥v1.3 ] |
avatarSpeakingEyeContact |
The average proportion of eye contact while speaking in the range [0,1]. Default is 0.5 . [≥v1.3 ] |
avatarSpeakingHeadMove |
The average proportion of head movement while speaking in the range [0,1]. Default is 0.5 . [≥v1.3 ] |
avatarIgnoreCamera |
If set to true , makes the avatar to ignore the camera and speak to whatever it is facing. Default is false . [≥v1.3 ] |
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. Default is 40 . [≥v1.3 ] |
listeningSilenceThresholdMs |
Silence detection duration in milliseconds. If the volume stays below the level for the set duration, a "stop" event is triggered. Default is 2000 . [≥v1.3 ] |
listeningSilenceDurationMax |
Maximum silence in milliseconds before "maxsilence" event is triggered. Default is 10000 . [≥v1.3 ] |
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. Default is 90 . [≥v1.3 ] |
listeningActiveThresholdMs |
Activity detection duration in milliseconds. If the volume stays above the set level for the set duration, a "start" event is triggered. Default is 400 . [≥v1.3 ] |
listeningActiveDurationMax |
Maximum activity in milliseconds before "maxactive" event is triggered. Default is 240000 . [≥v1.3 ] |
statsNode |
Parent DOM element for the three.js stats display. If null , don't use. Default is null . |
statsStyle |
CSS style for the stats element. If null , use the three.js default style. Default is 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);
}
});
The following table lists some of the key methods. See the source code for the rest:
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 know, they can be given in optional visemes , vtimes and vdurations arrays. The object also supports optional timed callbacks using markers and mtimes . The opt object can be used to set text-specific lipsyncLang . |
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 [≥v1.3 ] |
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. [≥v1.2 ] |
stopGesture([ms=1000]) |
Stop the gesture with ms transition time. [≥v1.2 ] |
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 . [≥v1.3 ] |
stopListening |
Stop listening the incoming audio. [≥v1.3 ] |
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.
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:
- 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
- Create the needed 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
-
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. -
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 posedance.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.
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.
[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
FOR HOBBYISTS:
-
Create your own full-body avatar free at https://readyplayer.me
-
Copy the given URL and add the following URL parameters in order to include all the needed morph targets:
morphTargets=ARKit,Oculus+Visemes,mouthOpen,mouthSmile,eyesClosed,eyesLookUp,eyesLookDown&textureSizeLimit=1024&textureFormat=png
Your final URL should look something like this:https://models.readyplayer.me/64bfa15f0e72c63d7c3934a6.glb?morphTargets=ARKit,Oculus+Visemes,mouthOpen,mouthSmile,eyesClosed,eyesLookUp,eyesLookDown&textureSizeLimit=1024&textureFormat=png
-
Use the URL to download the GLB file to your own web server.
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
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. |
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 |
- 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" }
- 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 thejwt
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>
- 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
- 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>
The steps that are common to all new languages:
- Create a new file named
lipsync-xx.mjs
wherexx
is your language code, and place the file in the./modules/
directory. The language module should have a class namedLipsyncXx
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
andwordsToVisemes
. 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
,times
anddurations
.- 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 invisemes
. 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 invisemes
. 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.
- Property
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.
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);
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. It 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 a dynamic bone, which
can be configured using the following properties:
Property | Description | Example |
---|---|---|
bone |
The name of the bone in your custom skeleton. Note that each dynamic bone must have a parent bone. | bone: "ponytail1" |
type |
|
type: "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]. |
stiffness: 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]. |
damping: 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 |
external: 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) |
limits: [null,null,[null,0.01],null] |
deltaLocal |
Local position translation [dx,dy,dz] in meters [m]. OPTIONAL, default null |
deltaLocal: [0,0.01,0] |
deltaWorld |
World position translation [dx,dy,dz] in meters [m]. OPTIONAL, default null |
deltaWorld: [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 |
pivot: 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 |
excludes: [ { 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 |
helper: 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.