Dysarthric speaker identification with different degrees of dysarthria severity using deep belief networks-Reference-Cited by-同舟云学术

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Dysarthric speaker identification with different degrees of dysarthria severity using deep belief networks

Published:2018-07-27 Issue:5 Volume:40 Page:643-652
ISSN:1225-6463
Container-title:ETRI Journal
language:en
Short-container-title:ETRI Journal

Author:

Farhadipour Aref¹^ORCID,Veisi Hadi²,Asgari Mohammad¹,Keyvanrad Mohammad Ali³

Affiliation:

1. Department of Media Engineering; IRI Broadcast University; Tehran Iran

2. Faculty of New Sciences and Technologies; University of Tehran; Tehran Iran

3. Department of Computer Engineering and Information Technology; Amirkabir University of Technology; Tehran Iran

Publisher

Wiley

Subject

Electrical and Electronic Engineering,General Computer Science,Electronic, Optical and Magnetic Materials

Link

http://onlinelibrary.wiley.com/wol1/doi/10.4218/etrij.2017-0260/fullpdf

Reference23 articles.

1. A perceptually-motivated low-complexity instantaneous linear channel normalization technique applied to speaker verification;Poblete,2015

2. Automatic intelligibility assessment of dysarthric speech using phonologically-structured sparse linear model;Kim;IEEE/ACM Trans. Audio, Speech, Lang. Process.,2015

3. A survey on perceived speaker traits: Personality, likability, pathology, and the first challenge;Schuller;Comput. Speech Lang.,2015

4. Fully automated speaker identification and intelligibility assessment in dysarthria disease using auditory knowledge;Kadi;Biocybernetics Biomed. Eng.,2016

Cited by 17 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. Pathological voice classification system based on CNN-BiLSTM network using speech enhancement and multi-stream approach;International Journal of Speech Technology;2024-06

2. Combined approach to dysarthric speaker verification using data augmentation and feature fusion;Speech Communication;2024-05

3. Analysis of Deep Generative Model Impact on Feature Extraction and Dimension Reduction for Short Utterance Text-Independent Speaker Verification;Circuits, Systems, and Signal Processing;2024-04-13

4. Gammatonegram representation for end-to-end dysarthric speech processing tasks: speech recognition, speaker identification, and intelligibility assessment;Iran Journal of Computer Science;2024-03-10

5. Constant Q Cepstral Coefficients for Automatic Speaker Verification System for Dysarthria Patients;Circuits, Systems, and Signal Processing;2023-09-23

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