LWMD: A Comprehensive Compression Platform for End-to-End Automatic Speech Recognition Models
Recently end-to-end (E2E) automatic speech recognition (ASR) models have achieved promising performance. However, existing models tend to adopt increasing model sizes and suffer from expensive resource consumption for real-world applications. To compress E2E ASR models and obtain smaller model sizes...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-01-01
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Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/13/3/1587 |