Non supervised neural net applied to the detection of voice impairment
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This paper is focussed in the task of detection of pathological voices by means of non-supervised neural nets (Kohonen self organising maps), comparing results ...
This paper is focussed in the task of detection of pathological voices by means of non supervised neural nets (Kohonen Self. Organising Maps), comparing results ...
Jul 19, 2023 · This study aims to summarize a comprehensive view of research on voice-affecting disorders that uses ML techniques for diagnosis and monitoring through voice ...
May 5, 2023 · Machine learning techniques can be used on the features of speech signals for the automatic detection of disorders.
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Sep 25, 2024 · The study aims to classify normal and pathological voices by leveraging the wav2vec 2.0 model as a feature extraction method in conjunction with machine ...
Jul 25, 2022 · The identification of PD based on vocal disorders is at the forefront of research. In this paper, an experimental study is performed on an open ...
Jul 19, 2023 · This study aims to summarize a comprehensive view of research on voice-affecting disorders that uses ML techniques for diagnosis and monitoring ...
Jun 3, 2024 · We propose an artificial intelligence method to effectively identify depression. The wav2vec 2.0 voice-based pre-training model was used as a feature extractor.
It has been suggested that AI/machine learning (ML) is useful in assisting clinicians with early and more accurate detection of voice disorders.
Jul 25, 2022 · In this paper, an experimental study is performed on an open source Kaggle PD speech dataset and novel comparative techniques were employed to identify PD.