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Speech perception at the interface of neurobiology and linguistics

机译:神经生物学和语言学交界处的语音感知

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Speech perception consists of a set of computations that take continuously varying acoustic waveforms as input and generate discrete representations that make contact with the lexical representations stored in long-term memory as output. Because the perceptual objects that are recognized by the speech perception enter into subsequent linguistic computation, the format that is used for lexical representation and processing fundamentally constrains the speech perceptual processes. Consequently, theories of speech perception must, at some level, be tightly linked to theories of lexical representation. Minimally, speech perception must yield representations that smoothly and rapidly interface with stored lexical items. Adopting the perspective of Marr, we argue and provide neurobiological and psychophysical evidence for the following research programme. First, at the implementational level, speech perception is a multi-time resolution process, with perceptual analyses occurring concurrently on at least two time scales (approx. 20 - 80 ms, approx. 150 - 300 ms), commensurate with (sub) segmental and syllabic analyses, respectively. Second, at the algorithmic level, we suggest that perception proceeds on the basis of internal forward models, or uses an 'analysis-by-synthesis' approach. Third, at the computational level (in the sense of Marr), the theory of lexical representation that we adopt is principally informed by phonological research and assumes that words are represented in the mental lexicon in terms of sequences of discrete segments composed of distinctive features. One important goal of the research programme is to develop linking hypotheses between putative neurobiological primitives (e.g. temporal primitives) and those primitives derived from linguistic inquiry, to arrive ultimately at a biologically sensible and theoretically satisfying model of representation and computation in speech.
机译:语音感知包括一组计算,这些计算将连续变化的声波波形作为输入,并生成与存储在长期存储器中的词汇表示形式接触的离散表示形式,作为输出。因为语音感知识别的感知对象会进入后续的语言计算,所以用于词汇表示和处理的格式从根本上限制了语音感知过程。因此,言语感知理论必须在某种程度上与词汇表征理论紧密联系。最低限度地,语音感知必须产生与存储的词汇项平滑且快速地交互的表示。我们采用Marr的观点进行争论,并为以下研究计划提供神经生物学和心理物理证据。首先,在实现水平上,语音感知是一个多时间分辨率的过程,在至少两个时间尺度(大约20-80毫秒,大约150-300毫秒)上同时进行感知分析,与(子)分段相称。和音节分析。其次,在算法层面,我们建议感知是基于内部前向模型进行的,或者使用“综合分析”的方法进行。第三,在计算水平上(在Marr的意义上),我们采用的词汇表述理论主要是由语音学研究提供的,并假设单词在心理词典中是根据具有独特特征的离散段的序列来表示的。该研究计划的一个重要目标是发展假定的神经生物学原语(例如时间原语)与那些源自语言探究的原语之间的联系假设,以最终形成一种生物学上合理的,理论上令人满意的语音表示和计算模型。

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