On the Mutual Information between Source and Filter Contributions for Voice Pathology Detection
원문 초록
This paper addresses the problem of automatic detection of voice pathologies directly from the speech signal. For this, we investigate the use of the glottal source estimation as a means to detect voice disorders. Three sets of features are proposed, depending on whether they are related to the speech or the glottal signal, or to prosody. The relevancy of these features is assessed through mutual information-based measures. This allows an intuitive interpretation in terms of discrimation power and redundancy between the features, independently of any subsequent classifier. It is discussed which characteristics are interestingly informative or complementary for detecting voice pathologies.
함께 살펴볼 논문
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MVP: Multi-source Voice Pathology detection
VoiceGRPO: Modern MoE Transformers with Group Relative Policy Optimization GRPO for AI Voice Health Care Applications on Voice Pathology Detection
Reproducible Machine Learning-based Voice Pathology Detection: Introducing the Pitch Difference Feature
Analysis and Detection of Pathological Voice using Glottal Source Features
Phase-based Information for Voice Pathology Detection
Towards Robust Voice Pathology Detection
토론
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