Microscopic modeling of hearing impaired listeners speech recognition using a physiologic auditory model

在嘈杂的环境中，语音清晰度下降是感觉神经性听障听众（最常见的听力障碍形式）最常见的抱怨之一。该项目的目的是为了更好地了解不同类型的感觉神经性听力障碍对人类语音识别的影响。所获得的知识将有利于新型助听器的设计。为了理解这个问题，我打算使用一种计算建模的方法来模拟听障听众的语音识别。语音和噪声的混合将由听觉外围模型处理，该模型为自动语音识别（ASR）系统提供输入。这种方法可以被称为微观语音识别模型，因为它对数字化时域信号（而不是对长期频谱）进行操作。这模拟了发生在人类听觉系统中的处理过程。此外，我打算建立单个音素的识别模型，而不是整个句子。提出的实验将取代以前在我的论文中使用的听觉模型与一个模型，模仿个人的生理阶段在听觉系统更接近。迄今为止，人类听觉处理仅以“有效”（现象学）的方式建模。埃塞克斯大学（University of Essex）开发的新的、更加生理性的听觉模型再现了听神经的放电模式，也就是中枢神经系统可以接触到的那些模式。选择埃塞克斯进行这项研究将允许我对听力受损的听众进行额外的语音识别实验，对他们来说，使用最近开发的新技术已经产生了对他们听力的非常精确的诊断。该地点的第二个优势是与谢菲尔德大学的“言语和听力”小组（全球领先的ASR研究）密切合作。

Degraded speech intelligibility is one of the most frequent complaints of sensorineural hearing-impaired listeners (the most common form of hearing impairment) in noisy situations. The aim of this project is to gain a better understanding of the impact of different types of sensorineural hearing impairment on human speech recognition. The knowledge obtained will be beneficial for the design of new hearing aids. I intend to use a computational modeling approach to model the speech recognition of hearing-impaired listeners in order to understand this problem. Mixtures of speech and noise will be processed by a model of the auditory periphery, which supplies the input to an automatic speech recognition (ASR) system. This approach can be termed a microscopic speech recognition model, because it operates on digitized time-domain signals (rather than operating on long-term spectra). This simulates the processing that takes place in the human auditory system. Furthermore, I intend to model the recognition of single phonemes rather than whole sentences. The proposed experiments will replace the previously in my dissertation used auditory model with a model that mimics individual physiological stages in the auditory system much more closely. Hitherto, human auditory processing was only modeled in an "effective" (phenomenological) way. The new, more physiological auditory model, developed at the University of Essex, reproduces auditory nerve firing patterns, i.e. those patterns that the central nervous system has access to.The choice of Essex for this research will allow me to do additional speech recognition experiments with hearing-impaired listeners, for whom a very precise diagnosis of their hearing has already been generated using recently developed new techniques. A second advantage of this location is a close cooperation with the „Speech and Hearing“ group at the University of Sheffield (worldwide leading in ASR research).