SPEAKER-DEPENDENT FEATURES FOR SPONTANEOUS SPEECH RECOGNITION

Autor:	I. P. Medennikov
Jazyk:	English<br />Russian
Rok vydání:	2016
Předmět:	automatic speech recognition speaker adaptation i-vectors bottleneck features from deep neural network Optics. Light QC350-467 Electronic computers. Computer science QA75.5-76.95
Zdroj:	Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki, Vol 16, Iss 1, Pp 195-197 (2016)
Druh dokumentu:	article
ISSN:	2226-1494 2500-0373
DOI:	10.17586/2226-1494-2016-16-1-195-197
Popis:	This paper presents the results of the study on improving robustness to the acoustic variability of the speech signal for spontaneous speech recognition system. The method is proposed to constructing high-level bottleneck features using deep neural network adapted to a speaker and to acoustic environment with i-vectors. The proposed method provides 11,9% relative reduction of word error rate in Russian spontaneous telephone speech recognition task.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/e7b30b1107b443fc9ff51ab14c033e57 Zobrazit plný text záznamu View record in DOAJ