@inproceedings{92437dc52e104c92be0e1faac53da573,
title = "Representation of phonemes in primary auditory cortex: How the brain analyzes speech",
abstract = "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.",
keywords = "Auditory system, Speech processing, Speech recognition",
author = "Nima Mesgarani and Stephen David and Shihab Shamma",
year = "2007",
doi = "10.1109/ICASSP.2007.367025",
language = "English (US)",
isbn = "1424407281",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "765--768",
booktitle = "2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07",
note = "2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07 ; Conference date: 15-04-2007 Through 20-04-2007",
}