An End-to-End Approach to Automatic Speech Assessment for People with Aphasia
Refereed conference paper presented and published in conference proceedings

香港中文大學研究人員
替代計量分析
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其它資訊
摘要Conventionally, automatic assessment of pathological speech involves two main steps: (1) extraction of pathology-specific features; (2) classification or regression of extracted features. Given the great variety of speech and language disorders, feature design is never a straightforward task, and yet it is most critical to the performance of assessment. This paper presents an end-to-end approach to automatic speech assessment for Cantonese-speaking people with aphasia (PWA). The assessment is formulated as a binary classification problem to differentiate PWA with high scores of subjective assessment from those with low scores. The sequence-to-one GRU-RNN and CNN models are applied to realize the end-to-end mapping from speech signals to the classification result. The speech features used for assessment are learned implicitly by the neural network model. Preliminary experimental results show that the end-to-end approach could reach a performance level comparable to conventional two-step approach. The experimental results also suggest that CNN performs better than sequence-toone GRU-RNN in this specific task.
著者Ying Qin, Tan Lee, Yuzhong Wu, Anthony Pak Hin Kong
會議名稱11th International Symposium on Chinese Spoken Language Processing (ISCSLP)
會議開始日26.11.2018
會議完結日29.11.2018
會議地點Taipei
會議國家/地區台灣
會議論文集題名2018 11th International Symposium on Chinese Spoken Language Processing (ISCSLP)
出版年份2018
月份11
出版社IEEE
出版地Taipei
頁次66 - 70
電子國際標準書號978-1-5386-5627-3
語言美式英語
關鍵詞Pathological speech assessment, end-to-end, Cantonese

上次更新時間 2021-01-05 於 01:23