DocumentCode
2268839
Title
Improving automatic speech recognition robustness for the Romanian language
Author
Buzo, Andi ; Cucu, Horia ; Burileanu, Corneliu
Author_Institution
Fac. of Electron., Telecommun. & Inf. Technol., Univ. “Politeh.” of Bucharest, Bucharest, Romania
fYear
2011
fDate
Aug. 29 2011-Sept. 2 2011
Firstpage
2119
Lastpage
2122
Abstract
In this paper we propose an alternative way of improving speech recognition accuracy by analyzing the relevance of voice feature dimensions. A new measure is defined in order to quantify the feature distribution overlapping. Based on this measure, weights for voice feature dimensions are calculated and then applied to the hypotheses resulted from an N-best recognition process. Experiments are made with an Automatic Speech Recognition (ASR) system for the Romanian language. A relative improvement of 22% is obtained in terms of Word Error Rate (WER).
Keywords
feature extraction; natural language processing; speech enhancement; speech recognition; ASR system; N-best recognition process; Romanian language; WER; automatic speech recognition robustness improvement; voice feature dimensions; voice feature distribution overlapping; word error rate; Accuracy; Databases; Equations; Hidden Markov models; Mathematical model; Speech recognition; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Signal Processing Conference, 2011 19th European
Conference_Location
Barcelona
ISSN
2076-1465
Type
conf
Filename
7074079
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