Kaldi Speech Recognition Toolkit

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.

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• 1 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.
• 2 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.
• 3 Kaldi is released under the Apache License v2.0, which is highly nonrestrictive, making it suitable for a wide community of users.

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

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