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Speech-to-Text Model Comparison #34

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@Cgarg9

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@Cgarg9

Description:

To help users understand different speech recognition methods, add a notebook that applies multiple models on the same dataset and compares results.

Tasks:

  • Compare CMU Sphinx, DeepSpeech, Wav2Vec 2.0, OpenAI Whisper.
  • Provide Word Error Rate (WER) and Sentence Error Rate (SER) comparisons.
  • Summarize key use cases and limitations for each model.
  • Name the notebook speech_to_text_comparison.ipynb.
  • Update the README file with relevant references.

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