Kaldi is a popular open-source toolkit for speech recognition, developed by researchers at Johns Hopkins University. It provides a wide range of tools for developing automatic speech recognition (ASR) systems, including acoustic and language modeling, decoding, alignment, and evaluation. Kaldi is written in C++ and provides a command line interface for accessing its functions. It uses state-of-the-art techniques for acoustic modeling, including deep neural networks (DNNs) and convolutional neural networks (CNNs), as well as advanced language modeling methods including n-grams and recurrent neural networks (RNNs). Kaldi is widely used in academic and industrial ASR research, and has been employed in a range of applications including keyword spotting, voice search, and voice-controlled smart home devices.
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