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How the Human Brain Recognizes Speech in the Context of Changing Speakers

机译:在说话者不断变化的背景下人脑如何识别语音

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摘要

We understand speech from different speakers with ease, whereas artificial speech recognition systems struggle with this task. It is unclear how the human brain solves this problem. The conventional view is that speech message recognition and speaker identification are two separate functions and that message processing takes place predominantly in the left hemisphere, whereas processing of speaker-specific information is located in the right hemisphere. Here, we distinguish the contribution of specific cortical regions, to speech recognition and speaker information processing, by controlled manipulation of task and resynthesized speaker parameters. Two functional magnetic resonance imaging studies provide evidence for a dynamic speech-processing network that questions the conventional view. We found that speech recognition regions in left posterior superior temporal gyrus/superior temporal sulcus (STG/STS) also encode speaker-related vocal tract parameters, which are reflected in the amplitude peaks of the speech spectrum, along with the speech message. Right posterior STG/STS activated specifically more to a speaker-related vocal tract parameter change during a speech recognition task compared with a voice recognition task. Left and right posterior STG/STS were functionally connected. Additionally, we found that speaker-related glottal fold parameters (e.g., pitch), which are not reflected in the amplitude peaks of the speech spectrum, are processed in areas immediately adjacent to primary auditory cortex, i.e., in areas in the auditory hierarchy earlier than STG/STS. Our results point to a network account of speech recognition, in which information about the speech message and the speaker's vocal tract are combined to solve the difficult task of understanding speech from different speakers.
机译:我们可以轻松地理解来自不同说话者的语音,而人工语音识别系统却难以完成这项任务。目前尚不清楚人脑如何解决这个问题。传统观点认为语音消息识别和说话人识别是两个独立的功能,并且消息处理主要发生在左半球,而说话人特定信息的处理则位于右半球。在这里,我们通过任务的控制操作和重新合成的说话人参数来区分特定皮质区域对语音识别和说话人信息处理的贡献。两项功能性磁共振成像研究为质疑传统观点的动态语音处理网络提供了证据。我们发现左后颞上回/颞上沟(STG / STS)中的语音识别区域还编码与说话者相关的声道参数,这些参数与语音消息一起反映在语音频谱的振幅峰值中。与语音识别任务相比,在语音识别任务期间,右后方STG / STS特别激活了说话人相关的声道参数变化。左右后STG / STS功能连接。此外,我们发现,与说话者相关的声门褶皱参数(例如音高)(未反映在语音频谱的振幅峰值中)在紧邻主听皮层的区域(即听觉层次中较早的区域)中进行处理。比STG / STS。我们的结果指向语音识别的网络帐户,其中将有关语音消息和说话人声道的信息组合在一起,以解决理解不同说话人语音的艰巨任务。

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