| Kaldi | |
| Developer: | Daniel Povey and others |
| Latest Release Version: | Revision 3122 |
| Repo: | https://github.com/kaldi-asr/kaldi |
| Programming Language: | C++ |
| Operating System: | Unix systems (Linux, BSD, OSX 10. etc.), Windows (via Cygwin) |
| Genre: | Speech recognition |
| License: | Apache License v.2.0[1] |
Kaldi is an open-source speech recognition toolkit written in C++ for speech recognition and signal processing, freely available under the Apache License v2.0.
Kaldi aims to provide software that is flexible and extensible,[2] and is intended for use by automatic speech recognition (ASR) researchers for building a recognition system.
It supports linear transforms, MMI, boosted MMI and MCE discriminative training, feature-space discriminative training, and deep neural networks.[3]
Kaldi is capable of generating features like mfcc, fbank, fMLLR, etc. Hence in recent deep neural network research, a popular usage of Kaldi is to pre-process raw waveform into acoustic feature for end-to-end neural models.
Kaldi has been incorporated as part of the CHiME Speech Separation and Recognition Challenge over several successive events.[4] [5] [6] The software was initially developed as part of a 2009 workshop at Johns Hopkins University.[7]
Kaldi is named after the legendary Ethiopian goat herder Kaldi who was said to have discovered the coffee plant.[8]