Cited by 4Stuttering Research and TreatmentSpeech Recognition and SynthesisVoice and Speech Disorders

Individual-independent and cross-language detection of speech disfluencies in stuttering based on multi-adversarial tasks and self-training

Shen, Jiakun, Zhang, Xueshuai·2025·Biomedical Signal Processing and Control

Integrity signals

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Crossref · 10.1016/j.bspc.2024.107051

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47 of 47 references verified0 citation errors · 0 not checkable

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  • Ground-truth or annotation-based verification was reported in a single study, where salient temporal regions identified by the explainability method were compared against reference labels provided by nonclinical annotators.

    “Ground-truth or annotation-based verification was reported in a single study [49], where salient temporal regions identified by the explainability method were compared against reference labels provided by nonclinical annotators.”

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Authors
Shen, J., & Zhang, X.
Affiliations
Chinese Academy of Sciences (CN)
Corresponding author
Zhang, Xueshuai
Venue
Biomedical Signal Processing and Control
Publisher
Elsevier BV
Published
2025-02
Volume
100
Pages
107051
ISSN
1746-8094 (ISSN-L)
OpenAlex
W4403525704
Cited by
2
References
51
Citations by year
2026: 1 · 2025: 1
FWCI
1.01
Type
journal article
Language
en
Open access
closed
Locations
Biomedical Signal Processing and Control (publishedVersion)
Topics
  • Social Sciences › Psychology › Clinical Psychology › Stuttering Research and Treatment
  • Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
  • Health Sciences › Medicine › Physiology › Voice and Speech Disorders
Keywords
stuttering, cross-language transfer, adversarial training, self-training, pseudo-labeling, Grad-CAM, wav2vec 2.0, speaker classification, language classification, German speech, English speech

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