EasyASR: A Distributed Machine Learning Platform for End-to-end Automatic Speech Recognition
We present EasyASR, a distributed machine learning platform for training and serving large-scale Automatic Speech Recognition (ASR) models, as well as collecting and processing audio data at scale. Our platform is built upon the Machine Learning Platform for AI of Alibaba Cloud. Its main functionality is to support efficient learning and inference for end-to-end ASR models on distributed GPU clusters. It allows users to learn ASR models with either pre-defined or user-customized network architectures via simple user interface. On EasyASR, we have produced state-of-the-art results over several public datasets for Mandarin speech recognition.
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Automatic Speech RecognitionAutomatic Speech Recognition (ASR)BIG-bench Machine LearningGPUspeech-recognitionSpeech RecognitionSimilar Papers 제목 키워드 기반
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