Representation of Phonemes in Primary Auditory Cortex: How the Brain Analyzes Speech

摘要

Many transformations inspired by the auditory system have improved the performance of automatic speech recognition (ASR) systems. However, humans perform substantially better than today''s ASR systems, suggesting that ASR systems can further benefit from understanding how the brain represents speech. To learn about the cortical representation of speech, we measured the neural responses in the primary auditory cortex to sentences from the TIMIT database. Here we examine how individual phonemes activate different subsets of auditory neurons, reflecting the diversity of neural tuning properties. We find that neurons with different spectro-temporal tuning provide an explicit multidimensional representation of articulatory features independent of speaker and context. This representation that matches the human perception could provide a framework for ASR in adverse conditions