2021
AAAI
AAAI 2021
EasyASR: A Distributed Machine Learning Platform for End-to-end Automatic Speech Recognition
Abstract
Abstract 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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Interdisciplinary Bridge
— Deep Learning and Machine Learning and Mathematics & Optimization and Speech & Audio
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Keyword Pioneer
— machine learning platform
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Machine Learning > Optimization & Theory > Distributed Learning
Machine Learning > Application Areas > Efficient Computing
Speech & Audio > Recognition > Automatic Speech Recognition
Mathematics & Optimization > Optimization > Distributed Learning
Deep Learning > Learning Types > Distributed Learning