Speech Recognition for Task Domains with Sparse Matched Training Data

Speech Recognition for Task Domains with Sparse Matched Training Data

We propose two approaches to handle speech recognition for task domains with sparse matched training data. One is an active learning method that selects training data for the target domain from another general domain that already has a significant amount of labeled speech data. This method uses attr...

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Bibliographic Details
Main Authors: Byung Ok Kang, Hyeong Bae Jeon, Jeon Gue Park
Format: Article
Language:English
Published: MDPI AG 2020-09-01
Series:Applied Sciences
Subjects:
automatic speech recognition
sparse training data
deep neural network
active learning
transfer learning
Online Access:https://www.mdpi.com/2076-3417/10/18/6155

Internet

https://www.mdpi.com/2076-3417/10/18/6155

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