TurnVoice 0.0.40

Replaces and translates voices in youtube videos

TurnVoice

A command-line tool to transform voices in YouTube videos with additional translation capabilities.[^1]

New Features

• Elevenlabs, OpenAI TTS, Azure, Coqui TTS and System voices for redubbing
• replace specific speaker or multiple speaker voices (work in progress)
• process local files
• preserve original background audio

more infos 👉 release notes

Prerequisites

• Rubberband command-line utility installed [^2]
• Deezer's Spleeter command-line utility installed [^3]
• Huggingface conditions accepted for Speaker Diarization and Segmentation
• Huggingface access token in env variable HF_ACCESS_TOKEN [^4]

[!TIP]

• For Deezer's Spleeter CLI install Python 3.8, then run pipx install spleeter --python /path/to/python3.8 (pip install pipx)
• 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 11.8
pip install torch==2.1.1+cu118 torchaudio==2.1.1+cu118 --index-url https://download.pytorch.org/whl/cu118

For CUDA 12.1
pip install torch==2.1.1+cu118 torchaudio==2.1.1+cu211 --index-url https://download.pytorch.org/whl/cu211

Usage

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

Example Command:

Arthur Morgan narrating a cooking tutorial:

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

[!NOTE] Requires a voice file (e.g., arthur.wav or .json) in the same directory (you find one in the tests directory).

Parameters Explained:

• -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: Synthesis engine (options: coqui, elevenlabs, azure, openai, system; default: coqui).
• -s, --speaker: Speaker number to be transformed.
• -snum, --num_speakers: Exact number of speakers in the video, aids in diarization.
• -smin, --min_speakers: Minimum number of speakers in the video.
• -smax, --max_speakers: Maximum number of speakers in the video.
• -dd, --download_directory: Directory for saving downloaded files (default: 'downloads').
• -sd, --synthesis_directory: Directory for saving synthesized audio files (default: 'synthesis').
• -exoff, --extractoff: Disables extraction of audio from the video file. Downloads audio and video from the internet.
• -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).

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

Coqui Engine

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

Voices (-v parameter)

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.

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

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

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

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

• 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 tech is not yet ready to be reliable
• translation feature is currently in experimental prototype state (powered by Meta's nllb-200-distilled-600m) 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

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

Future Improvements

• Tranlation quality: Add option to translate with OpenAI, DeepL API, other models. Better logic than simply transcribe the frags.
• Voice Cloning from YouTube: Cloning voices directly from other videos.
• Speed up to realtiem: Feed streams and get a "realtime" (translated) stream with voice of choice
• Open up the CLI: Allow local Videos, Audios and even Textfiles as Input until down to turnvoice "Hello World"
• match spoken volume of original voice

License

TurnVoice is proudly under the Coqui Public Model License 1.0.0 and NLLB-200 CC-BY-NC License (these are OpenSource NonCommercial licenses).

Let's Make It Fun! 🎉

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 ✨ 🌟 ✨

[^1]: State is work-in-progress (early pre-alpha), so please expect API changes to come and sometimes things not working properly yet. Developed on Python 3.11.4 under Win 10.
[^2]: Rubberband is needed to pitchpreserve timestretch audios for fitting synthesis into timewindow [^3]: Deezer's Spleeter is needed to split vocals for original audio preservation [^4]: Huggingface access token is needed to download the speaker diarization model for identifying speakers with pyannote.audio