Improved Broad Phonetic Classification and Segmentation with an Auditory Model

Autor:	Jean-Pierre Martens, L. Depuydt, L. Van Immerseel
Rok vydání:	1992
Předmět:	Artificial neural network business.industry Computer science Speech recognition Pattern recognition Instantaneous phase Dynamic programming Critical band Segmentation Artificial intelligence Adaptation (computer science) business Focus (optics) Envelope (motion)
Zdroj:	Speech Recognition and Understanding ISBN: 9783642766282
DOI:	10.1007/978-3-642-76626-8_32
Popis:	We describe a broad phonetic classification and segmentation algorithm based on neural networks and dynamic programming. The basics of our algorithm are outlined in another paper [7], so here we will focus on the introduction of auditory model features replacing the mel-scale parameters. Our auditory model incorporates critical band filtering, short time adaptation and temporal analysis of the auditory nerve responses. Unlike previously proposed synchrony models, it emphasizes the envelope rather than the instantaneous frequency as the carrier of perceptually relevant information.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::8004612dce91a6ecdf1cd9d05c2a44b9 https://doi.org/10.1007/978-3-642-76626-8_32 Zobrazit plný text záznamu