Employing Bottleneck and Convolutional Features for Speech-Based Physical Load Detection on Limited Data Amounts-Reference-Cited by-同舟云学术

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Employing Bottleneck and Convolutional Features for Speech-Based Physical Load Detection on Limited Data Amounts

Published:2019-09-15 Issue: Volume: Page:
ISSN:
Container-title:Interspeech 2019
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Author:

Egorow Olga,Mrech Tarik,Weißkirchen Norman,Wendemuth Andreas

Publisher

ISCA

Cited by 6 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. A physical exertion inspired multi-task learning framework for detecting out-of-breath speech;Computer Speech & Language;2024-03

2. Forecasting of Breathing Events from Speech for Respiratory Support;ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2023-06-04

3. Detection of Speech-based Physical Load Using Transfer Learning Approach;2021 IEEE 18th India Council International Conference (INDICON);2021-12-19

4. Analyzing the vocal tract characteristics for out-of-breath speech;The Journal of the Acoustical Society of America;2021-08

5. End-to-end Scalable and Low Power Multi-modal CNN for Respiratory-related Symptoms Detection;2020 IEEE 33rd International System-on-Chip Conference (SOCC);2020-09-08

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