MPSA-Conformer-CTC/Attention: A High-Accuracy, Low-Complexity End-to-End Approach for Tibetan Speech Recognition

MPSA-Conformer-CTC/Attention: A High-Accuracy, Low-Complexity End-to-End Approach for Tibetan Speech Recognition

This study addresses the challenges of low accuracy and high computational demands in Tibetan speech recognition by investigating the application of end-to-end networks. We propose a decoding strategy that integrates Connectionist Temporal Classification (CTC) and Attention mechanisms, capitalizing...

Full description

Saved in:
Bibliographic Details
Main Authors: Changlin Wu, Huihui Sun, Kaifeng Huang, Long Wu
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Sensors
Subjects:
Tibetan speech recognition
end-to-end models
conformer architecture
connectionist temporal classification (CTC)
Online Access:https://www.mdpi.com/1424-8220/24/21/6824
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/1424-8220/24/21/6824

Similar Items