Awesome
stream-translator
Command line utility to transcribe or translate audio from livestreams in real time. Uses streamlink to get livestream URLs from various services and OpenAI's whisper for transcription/translation. This script is inspired by audioWhisper which transcribes/translates desktop audio.
Prerequisites
- Install and add ffmpeg to your PATH
- Install CUDA on your system. If you installed a different version of CUDA than 11.3,
change cu113 in requirements.txt accordingly. You can check the installed CUDA version with
nvcc --version.
Setup
- Setup a virtual environment.
git clone https://github.com/fortypercnt/stream-translator.gitpip install -r requirements.txt- Make sure that pytorch is installed with CUDA support. Whisper will probably not run in real time on a CPU.
Command-line usage
python translator.py URL --flags
By default, the URL can be of the form twitch.tv/forsen and streamlink is used to obtain the .m3u8 link which is passed to ffmpeg.
See streamlink plugins for info on all supported sites.
| --flags | Default Value | Description |
|---|---|---|
--model | small | Select model size. See here for available models. |
--task | translate | Whether to transcribe the audio (keep original language) or translate to english. |
--language | auto | Language spoken in the stream. See here for available languages. |
--interval | 5 | Interval between calls to the language model in seconds. |
--history_buffer_size | 0 | Seconds of previous audio/text to use for conditioning the model. Set to 0 to just use audio from the last interval. Note that this can easily lead to repetition/loops if the chosen language/model settings do not produce good results to begin with. |
--beam_size | 5 | Number of beams in beam search. Set to 0 to use greedy algorithm instead (faster but less accurate). |
--best_of | 5 | Number of candidates when sampling with non-zero temperature. |
--preferred_quality | audio_only | Preferred stream quality option. "best" and "worst" should always be available. Type "streamlink URL" in the console to see quality options for your URL. |
--disable_vad | Set this flag to disable additional voice activity detection by Silero VAD. | |
--direct_url | Set this flag to pass the URL directly to ffmpeg. Otherwise, streamlink is used to obtain the stream URL. | |
--use_faster_whisper | Set this flag to use faster_whisper implementation instead of the original OpenAI implementation | |
--faster_whisper_model_path | whisper-large-v2-ct2/ | Path to a directory containing a Whisper model in the CTranslate2 format. |
--faster_whisper_device | cuda | Set the device to run faster-whisper on. |
--faster_whisper_compute_type | float16 | Set the quantization type for faster_whisper. See here for more info. |
Using faster-whisper
faster-whisper provides significant performance upgrades over the original OpenAI implementation (~ 4x faster, ~ 2x less memory). To use it, follow the instructions here to install faster-whisper and convert your models to CTranslate2 format. Then you can run the CLI with --use_faster_whisper and set --faster_whisper_model_path to the location of your converted model.