Shypd.aiThe largest open index of AI toolsEspresso is an open-source, modular, and extensible end-to-end neural automatic speech recognition (ASR) toolkit. It supports distributed training across GPUs and computing nodes, featuring various decoding approaches.
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Espresso is an open-source, modular, and extensible end-to-end neural automatic speech recognition (ASR) toolkit built upon the deep learning library PyTorch and the popular neural machine translation toolkit fairseq. It is designed to support distributed training across GPUs and computing nodes, making it suitable for large-scale ASR tasks. The toolkit incorporates various decoding approaches commonly used in ASR, including look-ahead word-based language model fusion, for which it implements a fast, parallelized decoder. Espresso provides state-of-the-art training recipes for prominent speech datasets like WSJ, LibriSpeech, and Switchboard, and has continuously evolved with features like CTC model training, Conformer encoder, Transducer models, and on-the-fly feature extraction from raw waveforms.
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