wscribe 0.1.0

Simple audio transcription tool using Whisper

* wscribe
** Getting started
*** Installation
Currently only tested on Linux, if you face any installation issues please feel free to [[https://github.com/geekodour/wscribe/issues][create issues]].
**** Set the required environment variables
- Set ~WSCRIBE_MODELS_DIR~ : Path to the directory where whisper models should be downloaded to
#+begin_src bash
export WSCRIBE_MODELS_DIR=$XDG_DATA_HOME/whisper-models # example
#+end_src
**** Download the models
- You can download the models directly [[https://huggingface.co/guillaumekln][from here]] using ~git lfs~, make sure you download/copy them to ~WSCRIBE_MODELS_DIR~
- Otherwise, you can just use the helper script at [[https://github.com/geekodour/wscribe/blob/main/scripts/fw_dw_hf_wo_lfs.sh][scripts/fw_dw_hf_wo_lfs.sh]], just download it and execute it as per its instructions.
**** Install package
Assuming you already have a working python setup
#+begin_src shell
pip install wscribe
#+end_src
** Usage
#+begin_src
Usage: wscribe transcribe [OPTIONS] SOURCE DESTINATION

  Transcribes SOURCE to DESTINATION. Where SOURCE can be local path to an
  audio file and DESTINATION needs to be a local path to a non-existing file

Options:
  -f, --format [json]             destication file format, currently only json
                                  is supported  [default: json]
  -m, --model [small|medium|large-v2]
                                  model should already be downloaded
                                  [default: medium]
  -g, --gpu                       enable gpu, disabled by default
  -d, --debug                     show debug logs
  --help                          Show this message and exit.
#+end_src
#+begin_src shell
wscribe transcribe audio.mp3 transcription.json # cpu
wscribe transcribe video.mp4 transcription.json --gpu # use gpu
#+end_src
** Contributing
All contribution happens through PRs, any contributions is greatly appreciated, bugfixes are welcome, features are welcome, tests are welcome, suggestions & criticism are welcome.
** Roadmap
- [-] Backends/Features
  - [X] faster-whisper
  - [ ] whisper.cpp
  - [ ] Add support for [[https://github.com/guillaumekln/faster-whisper/issues/303][diarization]]
  - [ ] Add VAD/other de-noising stuff etc.
  - [ ] Other GPU backends other than CUDA?
- [-] Inference UI
  - [X] CLI
    - [ ] statistics summary? time taken, playback speed vs transcription speed etc.
  - [ ] REST API
  - [ ] Streamlit UI
    - [ ] Would be nice to compare output of multiple models next to each other
- [ ] Editor UI
  - [ ] Web based offline editor
  - [ ] SRT and JSON editor
  - [ ] Play audio(2x/3x) and it'll highlight current text which can be edited
  - [ ] With wscribe JSON export, you'd also have the confidence score for each word color coded
- [-] Audio Source
  - [X] Local files
  - [ ] Youtube link
  - [ ] Google drive link
- [-] Distribution
  - [X] Python packaging
  - [ ] Windows support(?)
  - [ ] Package for Nix
  - [ ] Package for Arch(AUR)