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