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https://github.com/fortypercnt/stream-translator
https://github.com/fortypercnt/stream-translator
Last synced: 9 days ago
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- Host: GitHub
- URL: https://github.com/fortypercnt/stream-translator
- Owner: fortypercnt
- License: mit
- Created: 2022-10-02T01:38:40.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2023-03-19T17:13:51.000Z (over 1 year ago)
- Last Synced: 2024-08-02T11:24:44.847Z (3 months ago)
- Language: Python
- Size: 1.15 MB
- Stars: 220
- Watchers: 6
- Forks: 44
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# stream-translator
Command line utility to transcribe or translate audio from livestreams in real time. Uses [streamlink](https://github.com/streamlink/streamlink) to
get livestream URLs from various services and OpenAI's [whisper](https://github.com/openai/whisper) for transcription/translation.
This script is inspired by [audioWhisper](https://github.com/Awexander/audioWhisper) which transcribes/translates desktop audio.
## Prerequisites
1. [**Install and add ffmpeg to your PATH**](https://www.thewindowsclub.com/how-to-install-ffmpeg-on-windows-10#:~:text=Click%20New%20and%20type%20the,Click%20OK%20to%20apply%20changes.)
2. [**Install CUDA on your system.**](https://developer.nvidia.com/cuda-downloads) 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
1. Setup a virtual environment.
2. ```git clone https://github.com/fortypercnt/stream-translator.git```
3. ```pip install -r requirements.txt```
4. 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](https://streamlink.github.io/plugins.html) for info on all supported sites.
| --flags | Default Value | Description |
|:-------------------------------:|:---------------------:|:--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
| `--model` | small | Select model size. See [here](https://github.com/openai/whisper#available-models-and-languages) 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](https://github.com/openai/whisper#available-models-and-languages) 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](https://opennmt.net/CTranslate2/quantization.html) 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](https://github.com/guillaumekln/faster-whisper#installation) 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.