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Kaldi Speech Recognition Toolkit

📅 January 1, 2024 👤 Daniel Povey 📖 Infoscience (Ecole Polytechnique Fédérale de Lausanne) 📊 4,899 citations

🤖 Plain-English Summary

Abstract—We describe the design of Kaldi, a free, open-source toolkit for speech recognition research. Kaldi is written is C++, and the core library supports modeling of arbitrary phonetic-context sizes, acoustic modeling with subspace Gaussian mixture models (SGMM) as well as standard Gaussian mixture models, together with all commonly used linear and affine transforms.

🔑 Key Findings

  • Kaldi provides a speech recognition system based on finite-state transducers (using the freely available OpenFst), together with detailed documentation and scripts for building complete recognition systems.
  • Kaldi is written is C++, and the core library supports modeling of arbitrary phonetic-context sizes, acoustic modeling with subspace Gaussian mixture models (SGMM) as well as standard Gaussian mixture models, together with all commonly used linear and affine transforms.
  • Kaldi is released under the Apache License v2.0, which is highly nonrestrictive, making it suitable for a wide community of users.

💡 Why This Matters

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

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📋 Article Details

Category 🤖 Artificial Intelligence
Published Jan 01, 2024
Journal Infoscience (Ecole Polytechnique Fédérale de Lausanne)
Authors Daniel Povey
DOI 10.57702/jb3fvbn9
Citations 4,899
Source OpenAlex

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