# Listen: STT Services
This program is composed of two parts:
- A server aimed to be runned as a background service to serve STT models within the bounds of a socket.
- A client to query the models to transcribe audio from files or directly from a live microphone stream.
The outputed wav file can be stored for later use.
You can then use the `data.helper` script to verify the transcription of every wav file and update the CSV training register before you start training a model.
## Requirements
- [`python-pyaudio`](https://people.csail.mit.edu/hubert/pyaudio/)
## Installation
Once you have a working `pyaudio` for your version of python, install `listen`.
```zsh
pip install stt-listen
# Or from source
pip install git+https://gitlab.com/waser-technologies/technologies/listen.git
```
## Usage
```zsh
❯ listen --help
usage: listen [-h] [-f FILE] [--aggressive {0,1,2,3}] [-d MIC_DEVICE]
[-w SAVE_WAV]
Transcribe long audio files using webRTC VAD or use the streaming interface
from a microphone
options:
-h, --help show this help message and exit
-f FILE, --file FILE Path to the audio file to run (WAV format)
--aggressive {0,1,2,3}
Determines how aggressive filtering out non-speech is.
(Integer between 0-3)
-d MIC_DEVICE, --mic_device MIC_DEVICE
Device input index (Int) as listed by
pyaudio.PyAudio.get_device_info_by_index(). If not
provided, falls back to PyAudio.get_default_device().
-w SAVE_WAV, --save_wav SAVE_WAV
Path to directory where to save recorded sentences
--debug Show debug info
```
## Start the server
To use `listen`, you need a socket with STT models at the ready.
Example to enable as service.
```zsh
cp ./listen.service.example /usr/lib/systemd/user/listen.service
systemctl --user enable --now listen.service
```
Models for STT and punctuation will be downloaded the first time your run the server.
Or manually using python
```zsh
python -m listen.STT.as_service
```
### Get authorization to listen
You need to authorize the system to listen first. Change the service configuration as follows.
```toml
# ~/.assistant/stt.toml
...
[stt]
is_allowed = true
...
```
Then [start the server](#start-the-server) and use `listen` to start [transcribing audio](#use-the-client).
## Use the client
### Transcribe a file
You can quickly transcribe a wav file.
```zsh
❯ listen -f savewav_2022-04-11_17-18-08_578756.wav
Filename Duration(s)
savewav_2022-04-11_17-18-08_578756.wav 3.580
❯ cat savewav_2022-04-11_17-18-08_578756.txt
───────┬───────────────────────────────────────────────────────────────────────────────────────────────────────────────
│ File: savewav_2022-04-11_17-18-08_578756.txt
───────┼───────────────────────────────────────────────────────────────────────────────────────────────────────────────
1 │ Bonjour.
───────┴───────────────────────────────────────────────────────────────────────────────────────────────────────────────
```
### Transcribe from a live microphone stream
You can also query the models in real time from a microphone.
```zsh
❯ listen
You can speak now.
Bonjour.
^C
Stopped listening.
```
## Supported languages
By default, the server uses the system's language according to the environment variable `$LANG`.
You can manually specify a supported language for the server to use.
```zsh
LANG="en_US.UTF-8" python -m listen.STT.as_service
```
Have a look at [stt-models-locals](https://github.com/wasertech/stt-models-locals#languages) to see the complete list.
If the provided `$LANG` is not supported by any STT model, english is used as a failback.
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"description": "# Listen: STT Services\n\nThis program is composed of two parts:\n- A server aimed to be runned as a background service to serve STT models within the bounds of a socket.\n- A client to query the models to transcribe audio from files or directly from a live microphone stream.\n\n\nThe outputed wav file can be stored for later use.\n\nYou can then use the `data.helper` script to verify the transcription of every wav file and update the CSV training register before you start training a model.\n\n## Requirements\n\n- [`python-pyaudio`](https://people.csail.mit.edu/hubert/pyaudio/)\n\n## Installation\n\nOnce you have a working `pyaudio` for your version of python, install `listen`.\n\n```zsh\npip install stt-listen\n# Or from source\npip install git+https://gitlab.com/waser-technologies/technologies/listen.git\n```\n\n## Usage\n\n```zsh\n\u276f listen --help\nusage: listen [-h] [-f FILE] [--aggressive {0,1,2,3}] [-d MIC_DEVICE]\n [-w SAVE_WAV]\n\nTranscribe long audio files using webRTC VAD or use the streaming interface\nfrom a microphone\n\noptions:\n -h, --help show this help message and exit\n -f FILE, --file FILE Path to the audio file to run (WAV format)\n --aggressive {0,1,2,3}\n Determines how aggressive filtering out non-speech is.\n (Integer between 0-3)\n -d MIC_DEVICE, --mic_device MIC_DEVICE\n Device input index (Int) as listed by\n pyaudio.PyAudio.get_device_info_by_index(). If not\n provided, falls back to PyAudio.get_default_device().\n -w SAVE_WAV, --save_wav SAVE_WAV\n Path to directory where to save recorded sentences\n --debug Show debug info\n```\n\n## Start the server\n\nTo use `listen`, you need a socket with STT models at the ready.\n\nExample to enable as service.\n```zsh\ncp ./listen.service.example /usr/lib/systemd/user/listen.service\nsystemctl --user enable --now listen.service\n```\n\nModels for STT and punctuation will be downloaded the first time your run the server.\n\nOr manually using python\n\n```zsh\npython -m listen.STT.as_service\n```\n\n### Get authorization to listen\n\nYou need to authorize the system to listen first. Change the service configuration as follows.\n\n```toml\n# ~/.assistant/stt.toml\n...\n[stt]\nis_allowed = true\n...\n```\n\nThen [start the server](#start-the-server) and use `listen` to start [transcribing audio](#use-the-client).\n\n## Use the client\n\n### Transcribe a file\n\nYou can quickly transcribe a wav file.\n```zsh\n\u276f listen -f savewav_2022-04-11_17-18-08_578756.wav\nFilename Duration(s) \nsavewav_2022-04-11_17-18-08_578756.wav 3.580 \n\n\u276f cat savewav_2022-04-11_17-18-08_578756.txt\n\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n \u2502 File: savewav_2022-04-11_17-18-08_578756.txt\n\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u253c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n 1 \u2502 Bonjour.\n\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n```\n\n### Transcribe from a live microphone stream\n\nYou can also query the models in real time from a microphone.\n\n```zsh\n\u276f listen\nYou can speak now.\nBonjour.\n^C\nStopped listening.\n```\n\n## Supported languages\n\nBy default, the server uses the system's language according to the environment variable `$LANG`.\n\nYou can manually specify a supported language for the server to use.\n\n```zsh\nLANG=\"en_US.UTF-8\" python -m listen.STT.as_service\n```\n\nHave a look at [stt-models-locals](https://github.com/wasertech/stt-models-locals#languages) to see the complete list.\n\nIf the provided `$LANG` is not supported by any STT model, english is used as a failback.\n",
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