EasyASR: A Distributed Machine Learning Platform for End-to-end Automatic Speech Recognition

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 functionali...

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Hauptverfasser: Wang, Chengyu, Cheng, Mengli, Hu, Xu, Huang, Jun
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Computer Science - Artificial Intelligence
Computer Science - Computation and Language
Computer Science - Distributed, Parallel, and Cluster Computing
Computer Science - Learning
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creator Wang, Chengyu
Cheng, Mengli
Hu, Xu
Huang, Jun
description 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.
doi_str_mv 10.48550/arxiv.2009.06487
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subjects Computer Science - Artificial Intelligence
Computer Science - Computation and Language
Computer Science - Distributed, Parallel, and Cluster Computing
Computer Science - Learning
title EasyASR: A Distributed Machine Learning Platform for End-to-end Automatic Speech Recognition
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