ovos-stt-plugin-whisper-lm 0.0.6a9

A whisper stt plugin for OVOS

Description

OpenVoiceOS STT plugin for Whisper-LM-transformers, KenLM and Large language model integration with Whisper ASR models implemented in Hugging Face library.

Install

pip install ovos-stt-plugin-whisper-lm

⚠️ only python <=3.11 supported by some of the dependencies

Models

Pretrained ngram models are provided by HiTZ

Each lm_model is built using the KenLM toolkit and is based on n-gram statistics extracted from large, domain-specific corpora. The models available are:

• Basque (eu): 5gram-eu.bin (11G)
• Galician (gl): 5gram-gl.bin (8.4G)
• Catalan (ca): 5gram-ca.bin (20G)
• Spanish (es): 5gram-es.bin (13G)

Finetuned whisper models are also available from Xabier Zuazo for those languages

Instead of a ngram model it is also possible to use a LLM such as latxa

Configuration

In the example below, we use HiTZ Basque KenLM model. Optimize the lm_alpha, lm_beta, etc., for best results with your own models.

  "stt": {
    "module": "ovos-stt-plugin-whisper-lm",
    "ovos-stt-plugin-whisper-lm": {
        "model": "zuazo/whisper-medium-eu",
        "lm_repo": "HiTZ/whisper-lm-ngrams",
        "lm_model": "5gram-eu.bin",
        "lm_alpha": 0.33582369,
        "lm_beta": 0.68825565,
        "use_cuda": true
    }
  }

💡 lm_repo only needs to be set if you want to specify a specific filename in lm_model

To use an LLM instead of a ngram model

  "stt": {
    "module": "ovos-stt-plugin-whisper-lm",
    "ovos-stt-plugin-whisper-lm": {
        "model": "zuazo/whisper-medium-eu",
        "lm_model": "HiTZ/latxa-7b-v1.2",
        "lm_alpha": 2.73329396,
        "lm_beta": 0.00178595,
        "use_cuda": true
    }
  }

⚠️ Running large LMs side-by-side with Whisper requires sufficient GPU memory.

Credits

This plugin was developed by TigreGotico for OpenVoiceOS under the ILENIA project.

This plugin was funded by the Ministerio para la Transformación Digital y de la Función Pública and Plan de Recuperación, Transformación y Resiliencia - Funded by EU – NextGenerationEU within the framework of the project ILENIA with reference 2022/TL22/00215337

The pretrained Ngram models are available under the Creative Commons Attribution 4.0 International License (CC BY 4.0). You are free to use, modify, and distribute this model as long as you credit the original creators.

@misc{dezuazo2025whisperlmimprovingasrmodels,
      title={Whisper-LM: Improving ASR Models with Language Models for Low-Resource Languages}, 
      author={Xabier de Zuazo and Eva Navas and Ibon Saratxaga and Inma Hernáez Rioja},
      year={2025},
      eprint={2503.23542},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2503.23542}, 
}