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About A Comparative Study On Selecting Acoustic Modeling Units in Deep Neural Networks Based Large Vocabulary Chinese Speech Recognition
This document compares different acoustic modeling units in deep neural network (DNN)-based large vocabulary Chinese speech recognition systems. It finds that context dependent phones provide the best performance, while context independent syllables perform similarly to context dependent initial/finals units. The number of clustered states also impacts DNN performance differently than Gaussian mixture models. Additionally, multi-task learning can be used to combine multiple modeling units in DNN training, outperforming individual units.
Detailed Information
| Author: | ['Galaa Gantumur'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 6 |
| Language: | English |
| Format: | |
| Price: | FREE |
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