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Erschienen in:
Multimodal Human-Robot Interaction from the Perspective of a Speech Scientist Kapitel lesen Erstes Kapitel lesen

2015 | OriginalPaper | Buchkapitel

Improving Acoustic Models for Russian Spontaneous Speech Recognition

verfasst von : Alexey Prudnikov, Ivan Medennikov, Valentin Mendelev, Maxim Korenevsky, Yuri Khokhlov

Erschienen in: Speech and Computer

Verlag: Springer International Publishing

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Abstract

The aim of the paper is to investigate the ways to improve acoustic models for Russian spontaneous speech recognition. We applied the main steps of the Kaldi Switchboard recipe to a Russian dataset but obtained low accuracy with respect to the results for English spontaneous telephone speech. We found two methods to be especially useful for Russian spontaneous speech: the i-vector based deep neural network adaptation and speaker-dependent bottleneck features which provide 8.6 % and 11.9 % relative word error rate reduction over the baseline system respectively.

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Vorheriges Kapitel Gender Classification of Web Authors Using Feature Selection and Language Models
Nächstes Kapitel Information Sources of Word Semantics Methods
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Metadaten
Titel
Improving Acoustic Models for Russian Spontaneous Speech Recognition
verfasst von
Alexey Prudnikov
Ivan Medennikov
Valentin Mendelev
Maxim Korenevsky
Yuri Khokhlov
Copyright-Jahr
2015
Buch
Speech and Computer

Print ISBN: 978-3-319-23131-0

Electronic ISBN: 978-3-319-23132-7

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-3-319-23132-7_29