TurnVoice

A command-line tool to transform voices in (YouTube) videos with additional translation capabilities. ¹

Hint: Anybody interested in state-of-the-art voice solutions please also have a look at Linguflex. It lets you control your environment by speaking and is one of the most capable and sophisticated open-source assistants currently available.

Pulp.Fiction.Milkshake.Scene.mp4

Features

• Voice Transformation
  Turn voices with the free Coqui TTS at no operating costs ^{(supports voice cloning, 58 voices included}

• Voice Variety
  Support for popular TTS engines like Elevenlabs, OpenAI TTS, or Azure for more voices. ²

• Translation
  Translates videos at zero costs, for example from english to chinese. ^{powered by free deep-translator}

• Change Speaking Styles ^{(AI powered)}
  Make every spoken sentence delivered in a custom speaking style for a unique flair using prompting. ³

• Full Rendering Control
  Precise rendering control by customizing the sentence text, timings, and voice selection.

  ^{💡 Tip: the Renderscript Editor makes this step easy}

• Local Video Processing
  Process any local video files.

• Background Audio Preservation
  Keeps the original background audio intact.

Discover more in the release notes.

Prerequisites

Nvidia graphic card >8 GB VRAM recommended, tested on Python 3.11.4 / Windows 10.

• NVIDIA CUDA Toolkit 12.1 installed

  To install NVIDIA CUDA Toolkit:

  • Select operating system and version.
  • Download and install the software.

• NVIDIA cuDNN installed.

  To install NVIDIA cuDNN:

  - Download and install the software. (tested with v9.5.0, should also work with newer versions)

• Rubberband command-line utility installed ⁴

• ffmpeg command-line utility installed ⁵

  To install ffmpeg with a package manager:

  • On Ubuntu or Debian:

    sudo apt update && sudo apt install ffmpeg

  • On Arch Linux:

    sudo pacman -S ffmpeg

  • On MacOS using Homebrew (https://brew.sh/):

    brew install ffmpeg

  • On Windows using Chocolatey (https://chocolatey.org/):

    choco install ffmpeg

  • On Windows using Scoop (https://scoop.sh/):

    scoop install ffmpeg

• Huggingface conditions accepted for Speaker Diarization and Segmentation

• Huggingface access token in env variable HF_ACCESS_TOKEN ⁶

Tip

Set your HF token with `setx HF_ACCESS_TOKEN "your_token_here"

Installation

pip install turnvoice

Tip

For faster rendering with GPU prepare your CUDA environment after installation:

For CUDA 12.1
pip install torch==2.3.1+cu211 torchaudio==2.3.1+cu211 --index-url https://download.pytorch.org/whl/cu211

Rendering time is high even with a strong GPU, therefore while it might be possible it is not recommended to run this script on CPU only.

Note: Do not use torch versions >= 2.4 together with cuNN 9.0 because faster_whisper (CTranslate2) does not support this combination yet.

Usage

turnvoice [-i] <YouTube URL|ID|Local File> [-l] <Translation Language> -e <Engine(s)> -v <Voice(s)> -o <Output File>

Submit a string to the 'voice' parameter for each speaker voice you wish to use. If you specify engines, the voices will be assigned to these engines in the order they are listed. Should there be more voices than engines, the first engine will be used for the excess voices. In the absence of a specified engine, the Coqui engine will be used as the default. If no voices are defined, a default voice will be selected for each engine.

Example Command:

Arthur Morgan narrating a cooking tutorial:

turnvoice -i AmC9SmCBUj4 -v arthur.wav -o cooking_with_arthur.mp4

Note

Requires the cloning voice file (e.g., arthur.wav or .json) in the same directory (you find one in the tests directory).

Workflow

Preparation

Prepare a script with transcription, speaker diarization (and optionally translation or prompting) using:

turnvoice https://www.youtube.com/watch?v=cOg4J1PxU0c --prepare

Translation and prompts should be applied in this preparation step. Engines or voices come later in the render step.

Renderscript Editor

1. Open script
   Open the editor.html file. Click on the file open button and navigate to the folder you started turnvoice from. Open download folder. Open the folder with the name of the video. Open the file full_script.txt.
2. Edit
   The Editor will visualize the transcript and speaker diarization results and start playing the original video now. While playing verify texts, starting times and speaker assignments and adjust them if the detection went wrong.
3. Save
   Save the script. Remember the path to the file.

Rendering

Render the refined script to generate the final video using:

turnvoice https://www.youtube.com/watch?v=cOg4J1PxU0c --render <path_to_script>

Adjust the path in the displayed CLI command (the editor can't read that information out from the browser).

Assign engines and voices to each speaker track with the -e and -v commands.

Parameters

• -i, --in: Input video. Accepts a YouTube video URL or ID, or a path to a local video file.
• -l, --language: Language for translation. Coqui synthesis supports: en, es, fr, de, it, pt, pl, tr, ru, nl, cs, ar, zh, ja, hu, ko. Omit to retain the original video language.
• -il, --input_language: Language code for transcription, set if automatic detection fails.
• -v, --voice: Voices for synthesis. Accepts multiple values to replace more than one speaker.
• -o, --output_video: Filename for the final output video (default: 'final_cut.mp4').
• -a, --analysis: Print transcription and speaker analysis without synthesizing or rendering the video.
• -from: Time to start processing the video from.
• -to: Time to stop processing the video at.
• -e, --engine: Engine(s) to synthesize with. Can be coqui, elevenlabs, azure, openai or system. Accepts multiple values, linked to the the submitted voices.
• -s, --speaker: Speaker number to be transformed.
• -snum, --num_speakers: Helps diarization. Specify the exact number of speakers in the video if you know it in advance.
• -smin, --min_speakers: Helps diarization. Specify the minimum number of speakers in the video if you know it in advance.
• -smax, --max_speakers: Helps diarization. Specify the maximum number of speakers in the video if you know it in advance.
• -dd, --download_directory: Directory for saving downloaded files (default: 'downloads').
• -sd, --synthesis_directory: Directory for saving synthesized audio files (default: 'synthesis').
• -ex, --extract: Enables extraction of audio from the video file. Otherwise downloads audio from the internet (default).
• -c, --clean_audio: Removes original audio from the final video, resulting in clean synthesis.
• -tf, --timefile: Define timestamp file(s) for processing (functions like multiple --from/--to commands).
• -p, --prompt: Define a prompt to apply a style change to sentences like "speaking style of captain jack sparrow" ³
• -prep, --prepare: Write full script with speaker analysis, sentence transformation and translation but doesn't perform synthesis or rendering. Can be continued.
• -r, --render: Takes a full script and only perform synthesis and rendering on it, but no speaker analysis, sentence transformation or translation.
• -faster, --use_faster: Usage of faster_whisper for transcription. If stable_whisper transcription throws OOM errors or delivers suboptimal results. (Optional)
• -model, --model: Transcription model to be used. Defaults to large-v2. Can be 'tiny', 'tiny.en', 'base', 'base.en', 'small', 'small.en', 'medium', 'medium.en', 'large-v1', 'large-v2', 'large-v3', or 'large'. (Optional)

-i and -l can be used as both positional and optional arguments.

Translation

Translate a video into another language using the -l parameter.

For example, to translate into chinese you could use:

turnvoice https://www.youtube.com/watch?v=ZTH771HIhpg -l zh-CN -v daisy

^{Output Video
💡 Tip: In the tests folder you find a voice "chinese.json" trained on chinese phonemes.}

Languages for Coqui Engine

Shortcut	Language
ar	Arabic
cs	Czech
de	German
en	English
es	Spanish
fr	French
it	Italian
hu	Hungarian
ja	Japanese
ko	Korean
nl	Dutch
pl	Polish
pt	Portuguese
ru	Russian
tr	Turkish
zh-cn	Chinese

Languages for other engines

Make sure to select voice a supporting the language in Azure and System Engine.

Shortcut	Language
af	Afrikaans
sq	Albanian
am	Amharic
ar	Arabic
hy	Armenian
as	Assamese
ay	Aymara
az	Azerbaijani
bm	Bambara
eu	Basque
be	Belarusian
bn	Bengali
bho	Bhojpuri
bs	Bosnian
bg	Bulgarian
ca	Catalan
ceb	Cebuano
ny	Chichewa
zh-CN	Chinese (Simplified)
zh-TW	Chinese (Traditional)
co	Corsican
hr	Croatian
cs	Czech
da	Danish
dv	Dhivehi
doi	Dogri
nl	Dutch
en	English
eo	Esperanto
et	Estonian
ee	Ewe
tl	Filipino
fi	Finnish
fr	French
fy	Frisian
gl	Galician
ka	Georgian
de	German
el	Greek
gn	Guarani
gu	Gujarati
ht	Haitian Creole
ha	Hausa
haw	Hawaiian
iw	Hebrew
hi	Hindi
hmn	Hmong
hu	Hungarian
is	Icelandic
ig	Igbo
ilo	Ilocano
id	Indonesian
ga	Irish
it	Italian
ja	Japanese
jw	Javanese
kn	Kannada
kk	Kazakh
km	Khmer
rw	Kinyarwanda
gom	Konkani
ko	Korean
kri	Krio
ku	Kurdish (Kurmanji)
ckb	Kurdish (Sorani)
ky	Kyrgyz
lo	Lao
la	Latin
lv	Latvian
ln	Lingala
lt	Lithuanian
lg	Luganda
lb	Luxembourgish
mk	Macedonian
mai	Maithili
mg	Malagasy
ms	Malay
ml	Malayalam
mt	Maltese
mi	Maori
mr	Marathi
mni-Mtei	Meiteilon (Manipuri)
lus	Mizo
mn	Mongolian
my	Myanmar
ne	Nepali
no	Norwegian
or	Odia (Oriya)
om	Oromo
ps	Pashto
fa	Persian
pl	Polish
pt	Portuguese
pa	Punjabi
qu	Quechua
ro	Romanian
ru	Russian
sm	Samoan
sa	Sanskrit
gd	Scots Gaelic
nso	Sepedi
sr	Serbian
st	Sesotho
sn	Shona
sd	Sindhi
si	Sinhala
sk	Slovak
sl	Slovenian
so	Somali
es	Spanish
su	Sundanese
sw	Swahili
sv	Swedish
tg	Tajik
ta	Tamil
tt	Tatar
te	Telugu
th	Thai
ti	Tigrinya
ts	Tsonga
tr	Turkish
tk	Turkmen
ak	Twi
uk	Ukrainian
ur	Urdu
ug	Uyghur
uz	Uzbek
vi	Vietnamese
cy	Welsh
xh	Xhosa
yi	Yiddish
yo	Yoruba
zu	Zulu

Coqui Engine

Coqui engine is the default engine if no other engine is specified with the -e parameter.

To use voices from Coqui:

Voices (-v parameter)

You may either use one of the predefined coqui voices or clone your own voice.

Predefined Voices

To use a predefined voice submit the name of one of the following voices:

'Claribel Dervla', 'Daisy Studious', 'Gracie Wise', 'Tammie Ema', 'Alison Dietlinde', 'Ana Florence', 'Annmarie Nele', 'Asya Anara', 'Brenda Stern', 'Gitta Nikolina', 'Henriette Usha', 'Sofia Hellen', 'Tammy Grit', 'Tanja Adelina', 'Vjollca Johnnie', 'Andrew Chipper', 'Badr Odhiambo', 'Dionisio Schuyler', 'Royston Min', 'Viktor Eka', 'Abrahan Mack', 'Adde Michal', 'Baldur Sanjin', 'Craig Gutsy', 'Damien Black', 'Gilberto Mathias', 'Ilkin Urbano', 'Kazuhiko Atallah', 'Ludvig Milivoj', 'Suad Qasim', 'Torcull Diarmuid', 'Viktor Menelaos', 'Zacharie Aimilios', 'Nova Hogarth', 'Maja Ruoho', 'Uta Obando', 'Lidiya Szekeres', 'Chandra MacFarland', 'Szofi Granger', 'Camilla Holmström', 'Lilya Stainthorpe', 'Zofija Kendrick', 'Narelle Moon', 'Barbora MacLean', 'Alexandra Hisakawa', 'Alma María', 'Rosemary Okafor', 'Ige Behringer', 'Filip Traverse', 'Damjan Chapman', 'Wulf Carlevaro', 'Aaron Dreschner', 'Kumar Dahl', 'Eugenio Mataracı', 'Ferran Simen', 'Xavier Hayasaka', 'Luis Moray', 'Marcos Rudaski'

💡 Tip: simply write -v gracie as also parts of voice names are recognized and it's case-insensitive

Samples for every voice

Cloned Voices

Submit path to one or more audiofiles containing 16 bit 24kHz mono source material as reference wavs.

Example:

turnvoice https://www.youtube.com/watch?v=cOg4J1PxU0c -e coqui -v female.wav

The Art of Choosing a Reference Wav

• A 24000, 44100 or 22050 Hz 16-bit mono wav file of 10-30 seconds is your golden ticket.
• 24k mono 16 is my default, but I also had voices where I found 44100 32-bit to yield best results
• I test voices with this tool before rendering
• Audacity is your friend for adjusting sample rates. Experiment with frame rates for best results!

Fixed TTS Model Download Folder

Keep your models organized! Set COQUI_MODEL_PATH to your preferred folder.

Windows example:

setx COQUI_MODEL_PATH "C:\Downloads\CoquiModels"

Elevenlabs Engine

Note

To use Elevenlabs voices you need the API Key stored in env variable ELEVENLABS_API_KEY

All voices are synthesized with the multilingual-v1 model.

Caution

Elevenlabs is a pricy API. Focus on short videos. Don't let a work-in-progress script like this run unattended on a pay-per-use API. Bugs could be very annoying when occurring at the end of a pricy long rendering process.

To use voices from Elevenlabs:

Voices (-v parameter)

Submit name(s) of either a generated or predefined voice.

Example:

turnvoice https://www.youtube.com/watch?v=cOg4J1PxU0c -e elevenlabs -v Giovanni

Tip

Test rendering with a free engine like coqui first before using pricy ones.

OpenAI Engine

Note

To use OpenAI TTS voices you need the API Key stored in env variable OPENAI_API_KEY

To use voices from OpenAI:

Voice (-v parameter)

Submit name of voice. Currently only one voice for OpenAI supported. Alloy, echo, fable, onyx, nova or shimmer.

Example:

turnvoice https://www.youtube.com/watch?v=cOg4J1PxU0c -e openai -v shimmer

Azure Engine

Note

To use Azure voices you need the API Key for SpeechService resource in AZURE_SPEECH_KEY and the region identifier in AZURE_SPEECH_REGION

To use voices from Azure:

Voices (-v parameter)

Submit name(s) of either a generated or predefined voice.

Example:

turnvoice https://www.youtube.com/watch?v=BqnAeUoqFAM -e azure -v ChristopherNeural

System Engine

To use system voices:

Voices (-v parameter)

Submit name(s) of voices as string.

Example:

turnvoice https://www.youtube.com/watch?v=BqnAeUoqFAM -e system -v David

What to expect

• early alpha / work-in-progress, so bugs might occur (please report, need to be aware to fix)
• might not always achieve perfect lip synchronization, especially when translating to a different language
• speaker detection does not work that well, probably doing something wrong or or perhaps the tech⁷ is not yet ready to be reliable
• translation feature is currently in experimental prototype state (powered by deep-translate) and still produces very imperfect results
• occasionally, the synthesis might introduce unexpected noises or distortions in the audio (we got way better reducing artifacts with the new v0.0.30 algo)
• spleeter might get confused when a spoken voice and backmusic with singing are present together in the source audio

Source Quality

• delivers best results with YouTube videos featuring clear spoken content (podcasts, educational videos)
• requires a high-quality, clean source WAV file for effective voice cloning

Troubleshoot

If you run into "Could not locate cudnn_ops_infer64_8.dll", this is caused by faster_whisper not supporing the combination of cuDNN version greater than 9 and PyTorch version greater than 2.4.

To solve:

• Downgrade cuDNN to a version lower than 9 OR
• Downgrade PyTorch to a version lower than 2.4.

Pro Tips

How to exchange a single speaker

First perform a speaker analysis with -a parameter:

turnvoice https://www.youtube.com/watch?v=2N3PsXPdkmM -a

Then select a speaker from the list with -s parameter

turnvoice https://www.youtube.com/watch?v=2N3PsXPdkmM -s 2

License

TurnVoice is proudly under the Coqui Public Model License 1.0.0.

Contact 🤝

Share your funniest or most creative TurnVoice creations with me!

And if you've got a cool feature idea or just want to say hi, drop me a line on

• Twitter
• Reddit
• EMail

If you like the repo please leave a star
✨ 🌟 ✨

Footnotes

1. State is work-in-progress (early pre-alpha). Ülease expect CLI API changes to come and sorry in advance if anything does not work as expected.
   Developed on Python 3.11.4 under Win 10. ↩

2. Generates costs. Elevenlabs is pricy, OpenAI TTS, Azure are affordable. Needs API Keys stored in env variables, see engine information for details. ↩

3. Generates costs. Uses gpt-4-1106-preview model and needs OpenAI API Key stored in env variable OPENAI_API_KEY. ↩ ↩²

4. Rubberband is needed to pitchpreserve timestretch audios for fitting synthesis into timewindow. ↩

5. ffmpeg is needed to convert mp3 files into wav ↩

6. Huggingface access token is needed to download the speaker diarization model for identifying speakers with pyannote.audio. ↩

7. Speaker diarization is performed with the pyannote.audio default HF implementation on the vocals track splitted from the original audio. ↩