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https://github.com/hay/audio2text

Python command line utility wrappers for Whispercpp and other speech-to-text utilities
https://github.com/hay/audio2text

speech-recognition speech-to-text stt whisper whisper-cpp

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Python command line utility wrappers for Whispercpp and other speech-to-text utilities

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README 

        
# audio2text

> Python command line utility wrappers for Whispercpp and other speech-to-text utilities



## Introduction

This is mainly a set of useful scripts to automate Whispercpp processing, including:

* Automatic conversion of any video or audio format `ffmpeg` supports to the WAV format Whispercpp needs.

* Conversion of the transcripts to CSV, SRT, TXT, VTT and WTS (karaoke subtitles).



## Install

1. You need to have a working executable version of [whisper.cpp](https://github.com/ggerganov/whisper.cpp),

   you can either place that in the root of this repo as `whispercpp` or give the

   path using the `-w` flag

2. Place your models in the `models` folder. By default `audio2text.py` will

   look for `ggml-large.bin` in the models folder. You can also use the `-m` flag to give a path to the model.

3. `ffmpeg` is required and should be somewhere in your `$PATH`

4. You might want to make a virtual environment and then install the `requirements.txt`, e.g.



```bash

python -m venv .env

source .env/bin/activate

pip install -U pip

pip install -r requirements.txt

./audio2text.py

```



## Usage



### `audio2text.py`

To convert the given `berliner.ogg` file in the test directory to a CSV file (note that you don't need to give an extension)

```bash

./audio2text.py -i test/berliner.ogg -o test/berliner -of csv

```



If you want multiple output formats you can separate them by comma

```bash

./audio2text.py -i test/berliner.ogg -o test/berliner -of srt,txt

```



When giving the argument `all` to the `-of/--output-format` flag all Whisper-supported formats will be written

```bash

./audio2text.py -i test/berliner.ogg -o test/berliner -of all

```



To prevent duplication of all possible command line options for `whisper.cpp` you can use the `-wa` / `--whisper-args` flag to pass extra command line options to the whisper.cpp executable:



```bash

./audio2text.py -i test/berliner.ogg -o test/berliner -of csv -wa="--threads 8"

```



You can also use the `-u/--url` flag to give an URL to a MP3 file (or any other audio format `ffmpeg` supports). This will be downloaded to the `tmp` directory.



```bash

./audio2text.py -u https://www.bykr.org/test/berliner.mp3

```



To enable logging to a file use the `-lf/--log-file` flag, optionally combined with the `-v/--verbose` flag:



```bash

./audio2text.py -u https://www.bykr.org/test/berliner.mp3 -v -lf log.txt

```



To write all files and the log file to a non-existing directory you can use the `-od/--output-directory` flag:



```bash

./audio2text.py -u https://www.bykr.org/test/berliner.mp3 -of all -o out/text -v -lf out/log.log -od out

```



### `srtparse.py`

Converts SRT files to JSON, CSV and TXT using [dataknead](github.com/hay/dataknead).

```bash

./srtparse.py -i test/berliner.srt -o test/berliner.csv

```



## Troubleshooting

If you add the `-v` (verbose) flag `audio2text` will give much more debug information.



## All options

You'll get this when doing `audio2text.py -h`



```

usage: audio2text.py [-h] [-di] [-i INPUT] [-l LANGUAGE] [-lf LOG_FILE]

                     [-m MODEL_PATH] [-o OUTPUT] [-od OUTPUT_DIRECTORY]

                     [-of OUTPUT_FORMAT] [-kt] [-u URL] [-v] [-w WHISPER_PATH]

                     [-wa WHISPER_ARGS]



options:

  -h, --help            show this help message and exit

  -di, --diarize        Diarize audio (only works for natural stereo audio)

  -i INPUT, --input INPUT

                        Audio file to transcribe, anything that ffmpeg

                        supports will work

  -l LANGUAGE, --language LANGUAGE

                        Language of audio file, if not given Whisper will try

                        to autodetect this

  -lf LOG_FILE, --log-file LOG_FILE

                        Log messages to a logging file with this path, will

                        fail if the directory does not exist (use --od to

                        prevent that)

  -m MODEL_PATH, --model-path MODEL_PATH

                        Path to model you want to use for transcribing

  -o OUTPUT, --output OUTPUT

                        Path to output file, you don't need to give an

                        extension

  -od OUTPUT_DIRECTORY, --output-directory OUTPUT_DIRECTORY

                        When giving this argument, a directory will be created

                        before all other commands are run

  -of OUTPUT_FORMAT, --output-format OUTPUT_FORMAT

                        Output format, when giving 'all', all formats will be

                        used

  -kt, --keep-temp-files

                        Keep temporary files after transcribing (default is to

                        remove them)

  -u URL, --url URL     Give a URL to an audio file to download (e.g. mp3)

  -v, --verbose         Print debug information

  -w WHISPER_PATH, --whisper-path WHISPER_PATH

                        Path to the Whisper executable (defaults to

                        ./whispercpp)

  -wa WHISPER_ARGS, --whisper-args WHISPER_ARGS

                        Give a string of extra parameters to give to the

                        whisper executable

 ```



## License

MIT © [Hay Kranen](http://www.haykranen.nl)