How Does End-To-End Speech Recognition Training Impact Speech Enhancement Artifacts?-Reference-Cited by-同舟云学术

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How Does End-To-End Speech Recognition Training Impact Speech Enhancement Artifacts?

Published:2024-04-14 Issue: Volume: Page:11031-11035
ISSN:
Container-title:ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Iwamoto Kazuma¹,Ochiai Tsubasa²,Delcroix Marc²,Ikeshita Rintaro²,Sato Hiroshi²,Araki Shoko²,Katagiri Shigeru¹

Affiliation:

1. Doshisha University

2. NTT Corporation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10445798/10445803/10447750.pdf?arnumber=10447750

Reference26 articles.

1. Supervised Speech Separation Based on Deep Learning: An Overview

2. Performance measurement in blind audio source separation

3. An Algorithm for Intelligibility Prediction of Time–Frequency Weighted Noisy Speech

4. Perceptual evaluation of speech quality (PESQ)-a new method for speech quality assessment of telephone networks and codecs

5. The NTT CHiME-3 system: Advances in speech enhancement and recognition for mobile multi-microphone devices

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Speech emotion recognition in real static and dynamic human-robot interaction scenarios;Computer Speech & Language;2025-01

2. Rethinking Processing Distortions: Disentangling the Impact of Speech Enhancement Errors on Speech Recognition Performance;IEEE/ACM Transactions on Audio, Speech, and Language Processing;2024

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