Automatic Anomaly Detection for Dysarthria across Two Speech Styles: Read vs Spontaneous Speech
Perceptive evaluation of speech disorders is still the standard method in clinical practice for the diagnosing and the following of the condition progression of patients. Such methods include different tasks such as read speech, spontaneous speech, isolated words, sustained vowels, etc. In this context, automatic speech processing tools have proven pertinence in speech quality evaluation and assistive technology-based applications. Though, a very few studies have investigated the use of automatic tools on spontaneous speech. This paper investigates the behavior of an automatic phone-based anomaly detection system when applied on read and spontaneous French dysarthric speech. The behavior of the automatic tool reveals interesting inter-pathology differences across speech styles.
Code (0)
등록된 구현이 없습니다.
Tasks
Anomaly DetectionSimilar Papers 제목 키워드 기반
A study on the impact of Self-Supervised Learning on automatic dysarthric speech assessment
Automating dysarthria assessments offers the opportunity to develop practical, low-cost tools that address the current limitations of manual and subjective assessments. Nonetheless, the small size of most dysarthria data…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)ClassificationSelf-Supervised Learning+2A Multi-modal Approach to Dysarthria Detection and Severity Assessment Using Speech and Text Information
Automatic detection and severity assessment of dysarthria are crucial for delivering targeted therapeutic interventions to patients. While most existing research focuses primarily on speech modality, this study introduce…
Wav2vec-based Detection and Severity Level Classification of Dysarthria from Speech
Automatic detection and severity level classification of dysarthria directly from acoustic speech signals can be used as a tool in medical diagnosis. In this work, the pre-trained wav2vec 2.0 model is studied as a featur…
ClassificationMedical DiagnosisBrain Signals to Rescue Aphasia, Apraxia and Dysarthria Speech Recognition
In this paper, we propose a deep learning-based algorithm to improve the performance of automatic speech recognition (ASR) systems for aphasia, apraxia, and dysarthria speech by utilizing electroencephalography (EEG) fea…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)EEGElectroencephalogram (EEG)+2D\'etection automatique d'anomalies sur deux styles de parole dysarthrique: parole lue vs spontan\'ee (Automatic anomaly detection for dysarthria across two speech styles : read vs spontaneous speech)
L{'}{\'e}valuation perceptive de la parole pathologique reste le standard dans la pratique clinique pour le diagnostic et le suivi des patients. De telles m{\'e}thodes incluent plusieurs t{\^a}ches telles que la lecture,…
Anomaly DetectionDiagnostic