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Automatic speech recognition for acoustical analysis and assessment of cantonese pathological voice and speech

机译:关于声学分析的自动语音识别和粤语病理语音的评估

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This paper describes the application of state-of-the-art automatic speech recognition (ASR) systems to objective assessment of voice and speech disorders. Acoustical analysis of speech has long been considered a promising approach to non-invasive and objective assessment of people. In the past the types and amount of speech materials used for acoustical assessment were very limited. With the ASR technology, we are able to perform acoustical and linguistic analyses with a large amount of natural speech from impaired speakers. The present study is focused on Cantonese, which is a major Chinese dialect. Two representative disorders of speech production are investigated: dysphonia and aphasia. ASR experiments are carried out with continuous and spontaneous speech utterances from Cantonese-speaking patients. The results confirm the feasibility and potential of using natural speech for acoustical assessment of voice and speech disorders, and reveal the challenging issues in acoustic modeling and language modeling of pathological speech.
机译:本文介绍了最先进的自动语音识别(ASR)系统对语音和语音障碍的客观评估。言论的声学分析已经被认为是对人民无侵入性和客观评估的有希望的方法。过去,用于声学评估的语音材料的类型和数量非常有限。通过ASR技术,我们能够从扬声器受损的大量自然演讲进行声学和语言分析。本研究专注于广东话,这是一个主要的中文方言。调查了两种代表性的语音生产障碍:呼吸困难和失语症。 ASR实验是通过来自粤语患者的连续和自发的言语表达进行的。结果证实了使用语音和语音障碍声学评估的自然语音的可行性和潜力,并揭示了声学言论语言建模中的挑战性问题。

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