🎥 SoniTranslate 🈷️

🎬 Video Translation with Synchronized Audio 🌐

SonyTranslate is a powerful and user-friendly web application that allows you to easily translate videos into different languages. This repository hosts the code for the SonyTranslate web UI, which is built with the Gradio library to provide a seamless and interactive user experience.

Description	Link
📙 Colab Notebook
🎉 Repository
🚀 Online DEMO

SonyTranslate's web UI, which features a browser interface built on the Gradio library.

Supported languages for translation

Language Code	Language
en	English
fr	French
de	German
es	Spanish
it	Italian
ja	Japanese
nl	Dutch
uk	Ukrainian
pt	Portuguese
ar	Arabic
zh	Chinese - Simplified
zh-TW	Chinese - Traditional
cs	Czech
da	Danish
fi	Finnish
el	Greek
he	Hebrew
hu	Hungarian
ko	Korean
fa	Persian
pl	Polish
ru	Russian
tr	Turkish
ur	Urdu
hi	Hindi
vi	Vietnamese
id	Indonesian
bn	Bengali
te	Telugu
mr	Marathi
ta	Tamil
jw (or jv)	Javanese
ca	Catalan
ne	Nepali
th	Thai
sv	Swedish
am	Amharic
cy	Welsh
hr	Croatian
is	Icelandic
ka	Georgian
km	Khmer
sk	Slovak
sq	Albanian
sr	Serbian
az	Azerbaijani
bg	Bulgarian
gl	Galician
gu	Gujarati
kk	Kazakh
kn	Kannada
lt	Lithuanian
lv	Latvian
ml	Malayalam
ro	Romanian
si	Sinhala
su	Sundanese
et	Estonian
mk	Macedonian
sw	Swahili
af	Afrikaans
bs	Bosnian
la	Latin
my	Myanmar Burmese
no	Norwegian
as	Assamese
eu	Basque
ha	Hausa
ht	Haitian Creole
hy	Armenian
lo	Lao
mg	Malagasy
mn	Mongolian
mt	Maltese
pa	Punjabi
ps	Pashto
sl	Slovenian
sn	Shona
so	Somali
tg	Tajik
tk	Turkmen
tt	Tatar
uz	Uzbek
yo	Yoruba

Non-transcription

Language Code	Language
ay	Aymara
bm	Bambara
ceb	Cebuano
ny	Chichewa
dv	Divehi
doi	Dogri
ee	Ewe
gn	Guarani
ilo	Iloko
rw	Kinyarwanda
kri	Krio
ku	Kurdish
ky	Kirghiz
lg	Ganda
mai	Maithili
or	Oriya
om	Oromo
qu	Quechua
sm	Samoan
ti	Tigrinya
ts	Tsonga
ak	Akan
ug	Uighur

Example:

Original audio

Video_t.mp4

Translated audio

video_dub.mp4

Colab Runtime

To run SoniTranslate using Colab Runtime:

Install Locally (Installation tested in Linux)

Before You Start

Before you start installing and using SoniTranslate, there are a few things you need to do:

1. Install the NVIDIA drivers for CUDA 11.8.0, NVIDIA CUDA is a parallel computing platform and programming model that enables developers to use the power of NVIDIA graphics processing units (GPUs) to speed up compute-intensive tasks. You can find the drivers here. Follow the instructions on the website to download and install the drivers.
2. Accept the license agreement for using Pyannote. You need to have an account on Hugging Face and accept the license to use the models: https://huggingface.co/pyannote/speaker-diarization and https://huggingface.co/pyannote/segmentation
3. Create a huggingface token. Hugging Face is a natural language processing platform that provides access to state-of-the-art models and tools. You will need to create a token in order to use some of the automatic model download features in SoniTranslate. Follow the instructions on the Hugging Face website to create a token.
4. Install Anaconda. Anaconda is a free and open-source distribution of Python and R. It includes a package manager called conda that makes it easy to install and manage Python environments and packages. Follow the instructions on the Anaconda website to download and install Anaconda on your system.
5. Install Git for your system. Git is a version control system that helps you track changes to your code and collaborate with other developers. You can install Git with Anaconda by running conda install -c anaconda git -y in your terminal (Do this after step 1 in the following section.). If you have trouble installing Git via Anaconda, you can use the following link instead:
   • Git for Linux

Once you have completed these steps, you will be ready to install SoniTranslate.

Getting Started

To install SoniTranslate, follow these steps:

1. Create a suitable anaconda environment for SoniTranslate and activate it:

conda create -n sonitr python=3.10 -y
conda activate sonitr
conda install pytorch torchvision torchaudio pytorch-cuda=11.8 -c pytorch -c nvidia

2. Clone this github repository and navigate to it:

git clone https://github.com/r3gm/SoniTranslate.git
cd SoniTranslate

3. Install required packages:

pip install -r requirements_base.txt -v
pip install -r requirements_extra.txt -v
pip install onnxruntime-gpu

4. Install ffmpeg. FFmpeg is a free software project that produces libraries and programs for handling multimedia data. You will need it to process audio and video files. You can install ffmpeg with Anaconda by running conda install -y ffmpeg in your terminal. If you have trouble installing ffmpeg via Anaconda, you can use the following link instead: (https://ffmpeg.org/ffmpeg.html). Once it is installed, make sure it is in your PATH by running ffmpeg -h in your terminal. If you don't get an error message, you're good to go.

5. Optional install:

After installing FFmpeg, you can install these optional packages.

Piper TTS is a fast, local neural text to speech system that sounds great and is optimized for the Raspberry Pi 4. Piper is used in a variety of projects. Voices are trained with VITS and exported to the onnxruntime.

pip install -q piper-tts==1.2.0

Coqui XTTS is a text-to-speech (TTS) model that lets you generate realistic voices in different languages. It can clone voices with just a short audio clip, even speak in a different language! It's like having a personal voice mimic for any text you need spoken.

pip install -q -r requirements_xtts.txt
pip install -q TTS==0.21.1  --no-deps

Running SoniTranslate

To run SoniTranslate locally, make sure the sonitr conda environment is active:

conda activate sonitr

Setting your Hugging Face token as an environment variable in Linux:

export YOUR_HF_TOKEN="YOUR_HUGGING_FACE_TOKEN"

Then navigate to the SoniTranslate folder and run either the app_rvc.py

python app_rvc.py

When the local URL http://127.0.0.1:7860 is displayed in the terminal, simply open this URL in your web browser to access the SoniTranslate interface.

Stop and close SoniTranslate.

In most environments, you can stop the execution by pressing Ctrl+C in the terminal where you launched the script app_rvc.py. This will interrupt the program and stop the Gradio app. To deactivate the Conda environment, you can use the following command:

conda deactivate

This will deactivate the currently active Conda environment sonitr, and you'll return to the base environment or the global Python environment.

Starting Over

If you need to start over from scratch, you can delete the SoniTranslate folder and remove the sonitr conda environment with the following set of commands:

conda deactivate
conda env remove -n sonitr

With the sonitr environment removed, you can start over with a fresh installation.

Command line arguments

The app_rvc.py script supports command-line arguments to customize its behavior. Here's a brief guide on how to use them:

Argument command	Default	Value	Description
--theme	Taithrah/Minimal	String	Sets the theme for the interface. Themes can be found in the Theme Gallery.
--language	english	String	Selects the interface language. Available options: arabic, azerbaijani, chinese_zh_cn, english, french, german, hindi, indonesian, italian, japanese, korean, marathi, polish, portuguese, russian, spanish, swedish, turkish, ukrainian, vietnamese.
--verbosity_level	info	String	Sets the verbosity level of the logger: debug, info, warning, error, or critical.
--public_url		Boolean	Enables a public link.
--cpu_mode		Boolean	Enable CPU mode to run the program without utilizing GPU acceleration.
--logs_in_gui		Boolean	Shows the operations performed in Logs (obsolete).

Example usage:

python app_rvc.py --theme aliabid94/new-theme --language french

This command sets the theme to a custom theme and selects French as the interface language. Feel free to customize these arguments according to your preferences and requirements.

📖 News

🔥 2024/18/05: New Update Details

• Added option Overlap Reduction
• OpenAI API Key Integration for Transcription, translation, and TTS
• More output types: subtitles by speaker, separate audio sound, and video only with subtitles
• Access to a better-performing version of Whisper for transcribing speech on the Hugging Face Whisper page. Copy the repository ID and paste it into the 'Whisper ASR model' section in 'Advanced Settings'; e.g., kotoba-tech/kotoba-whisper-v1.1 for Japanese transcription available here
• Support for ASS subtitles and batch processing with subtitles
• Vocal enhancement before transcription
• Added CPU mode with app_rvc.py --cpu_mode
• TTS now supports up to 12 speakers
• OpenVoiceV2 integration for voice imitation
• PDF to videobook (displays images from the PDF)
• GUI language translation in Persian and Afrikaans
• New Language Support:
  • Complete support: Estonian, Macedonian, Malay, Swahili, Afrikaans, Bosnian, Latin, Myanmar Burmese, Norwegian, Traditional Chinese, Assamese, Basque, Hausa, Haitian Creole, Armenian, Lao, Malagasy, Mongolian, Maltese, Punjabi, Pashto, Slovenian, Shona, Somali, Tajik, Turkmen, Tatar, Uzbek, and Yoruba
  • Non-transcription: Aymara, Bambara, Cebuano, Chichewa, Divehi, Dogri, Ewe, Guarani, Iloko, Kinyarwanda, Krio, Kurdish, Kirghiz, Ganda, Maithili, Oriya, Oromo, Quechua, Samoan, Tigrinya, Tsonga, Akan, and Uighur

🔥 2024/03/02: Preserve file names in output. Multiple archives can now be submitted simultaneously by specifying their paths, directories or URLs separated by commas. Processing of a full YouTube playlist. About supported sites URL, please be aware that not all sites may work optimally. Added option for disabling diarization. Implemented soft subtitles. Format output (MP3, MP4, MKV, WAV, and OGG), and resolved issues related to file reading and diarization.

🔥 2024/02/22: Added freevc for voice imitation, fixed voiceless track, divide segments. New languages support (Swedish, Amharic, Welsh, Croatian, Icelandic, Georgian, Khmer, Slovak, Albanian, Serbian, Azerbaijani, Bulgarian, Galician, Gujarati, Kazakh, Kannada, Lithuanian, Latvian, Malayalam, Romanian, Sinhala and Sundanese). New translations of the GUI (Spanish, French, German, Italian, Japanese, Chinese Simplified, Ukrainian, Arabic, Russian, Turkish, Indonesian, Portuguese, Hindi, Vietnamese, Polish, Swedish, Korean, Marathi and Azerbaijani). With subtitle file, no align and the media file is not needed to process the SRT file. Burn subtitles to video. Queue can accept multiple tasks simultaneously. Sound alert notification. Continue process from last checkpoint. Acceleration rate regulation.

🔥 2024/01/16: Expanded language support (Thai, Nepali, Catalan, Javanese, Tamil, Marathi, Telugu, Bengali and Indonesian), the introduction of whisper large v3, configurable GUI options, integration of BARK, Facebook-mms, Coqui XTTS, and Piper-TTS. Additional features included audio separation utilities, XTTS WAV creation, use an SRT file as a base for translation, document translation, manual speaker editing, and flexible output options (video, audio, subtitles).

🔥 2023/10/29: Edit the translated subtitle, download it, adjust volume and speed options.

🔥 2023/08/03: Changed default options and added directory view of downloads.

🔥 2023/08/02: Added support for Arabic, Czech, Danish, Finnish, Greek, Hebrew, Hungarian, Korean, Persian, Polish, Russian, Turkish, Urdu, Hindi, and Vietnamese languages. 🌐

🔥 2023/08/01: Add options for use RVC models.

🔥 2023/07/27: Fix some bug processing the video and audio.

🔥 2023/07/26: New UI and add mix options.

Contributing

Welcome to contributions from the community! If you have any ideas, bug reports, or feature requests, please open an issue or submit a pull request. For more information, please refer to the contribution guidelines.

Credits

This project leverages a number of open-source projects. We would like to acknowledge and thank the contributors of the following repositories:

• PyTorch
• yt-dlp
• Gradio
• edge-tts
• deep-translator
• pyannote-audio
• WhisperX
• faster-whisper
• CTranslate2
• Transformers
• FFmpeg
• Piper
• Coqui TTS
• pypdf
• OpenVoice

License

Although the code is licensed under Apache 2, the models or weights may have commercial restrictions, as seen with pyannote diarization.