Towards Articulatory-Based Adaptation in Dysarthric Speech Recognition

自动语音识别（ASR）已经为普通大众提供了成熟和广泛的工具，但对于患有严重语音障碍的个人来说仍然无法有效使用。其中一组称为构音障碍的疾病是由神经肌肉疾病引起的，如脑瘫、多发性硬化症、帕金森病、中风。虽然患有构音障碍的人可能能够形成和理解完整的句子，但他们对讲话中使用的肌肉缺乏控制，产生无法理解的讲话。导致构音障碍的神经损伤也影响其他身体活动，例如与常规用户相比，在严重情况下使键盘输入减慢150至300倍（Hosom等人，2003; Hux等人，2000年）。如果可以可靠地识别出较差的语音，语音识别有可能成为键盘输入的可行替代方案。

Automatic speech recognition (ASR) has produced mature and widespread tools for the general public, but remains effectively unusable by individuals with severe speech disorders. One group of such disorders, called dysarthria, is caused by neuromuscular disorders such as cerebral palsy, multiple sclerosis, Parkinson's disease, stroke. While individuals with dysarthria might be able to form and comprehend full sentences, they would lack control over the muscles used in speech, producing unintelligible speech. The neurological damage that causes dysarthria also affects other physical activity, such as slowing keyboard input 150 to 300 fold in severe cases compared with regular users (Hosom et al., 2003; Hux et al., 2000). Speech recognition has the potential to be a viable alternative to keyboard input if poor speech can be reliably recognized.