This repository contains a fine-tuned Whisper Large V3 model for Russian speech recognition. It serves as the core transcription component of the Pisets system, specifically optimized for long audio recordings such as lectures and interviews.

The model was presented in the paper Pisets: A Robust Speech Recognition System for Lectures and Interviews.

System Architecture

The Pisets system implements a three-component architecture to improve recognition accuracy while minimizing hallucinations:

Wav2Vec2: For primary recognition and segmentation.
Audio Spectrogram Transformer (AST): For filtering non-speech segments.
Whisper (this model): For the final high-quality transcription.

Implementation

The complete source code and instructions for using the system (including generation of SRT and DocX files) can be found in the GitHub repository:

GitHub: https://github.com/bond005/pisets

Citation

If you use this model or the Pisets system in your research, please cite:

bibtex

@article{bondarenko2026pisets,
  title={Pisets: A Robust Speech Recognition System for Lectures and Interviews},
  author={Ivan Bondarenko},
  journal={arXiv preprint arXiv:2601.18415},
  year={2026}
}

bond005/whisper-large-v3-ru-podlodka

Whisper Large V3 Russian Podlodka

System Architecture

Implementation

Citation

bond005/
whisper-large-v3-ru-podlodka