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Dhivehi subtitle generator

The process follows a few basic steps:

  • Extract audio from the video
  • Download STT pretrained model and setup inference pipeline
  • Run STT on the audio to transcribe the audio
  • generate a .srt file containing subtitles with timestamps

Setup

  • Clone the repo

  • create virtual env py -m venv env

  • activate vertual env .\env\Scripts\Activate

  • Install requirements pip install -r requirements.txt

  • you may need to setup FFmpeg locally

Usage

The transcriber script requires an audio file as input.
You can use the provided audio_extract.py to extract audio from an input video file, and run further pre-processing on the file. Ex: run it through RNNoise or Spleeter.

usage: audio_extract.py input output

positional arguments:
  input                 Input video file eg: video.mp4
  output                Output file name eg: audio.wav

Afterwards, run dhivehi.py with the following arguments

The script uses pyAudioAnalysis to segment audio into more manageable lengths by running a silence detection routine. For better results, you might want to play around with the silence_window and silence_weight options, until the segmented audio looks good.

Two sample audio files included inside /audio

usage: dhivehi.py input output

eg: dhivehi.py .\audio\1.mp3 1.srt

positional arguments:
  input                 Input audio file name
  output                Output file name

optional arguments:
  -h, --help            show this help message and exit
  --model_dir MODEL_DIR
                        STT model files directory
  --temp_dir TEMP_DIR   Temp files directory
  --silence_window SILENCE_WINDOW
                        Audio smoothing window
  --silence_weight SILENCE_WEIGHT
                        Audio silence probabilistic weight

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Dhivehi audio to subtitle

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