Noisy Speech Recognition Based on Combined Audio-Visual Classifiers

Autor:	Juan Carlos Gómez, Marianela Parodi, Gonzalo D. Sad, Lucas D. Terissi
Rok vydání:	2015
Předmět:	Structure (mathematical logic) Range (mathematics) Computer science Speech recognition Audio visual Recognition system Word (computer architecture)
Zdroj:	Lecture Notes in Computer Science ISBN: 9783319148984 MPRSS Marianela Parodi
DOI:	10.1007/978-3-319-14899-1_5
Popis:	An isolated word speech recognition system based on audio-visual features is proposed in this paper. To enhance the recognition over different noisy conditions, this system combines three classifiers based on audio, visual and audio-visual information, respectively. The performance of the proposed recognition system is evaluated over two isolated word audio-visual databases, a public one and a database compiled by the authors of this paper. Experimental results show that the structure of the proposed system leads to significant improvements of the recognition rates through a wide range of signal-to-noise ratios.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::747dc9d0fd716e91e69fef1643384e29 https://doi.org/10.1007/978-3-319-14899-1_5 Zobrazit plný text záznamu