Publication result detail

Robust Speech Recognition in Unknown Reverberant and Noisy Conditions

HSIAO, R.; MA, J.; HARTMANN, W.; KARAFIÁT, M.; GRÉZL, F.; BURGET, L.; SZŐKE, I.; ČERNOCKÝ, J.; WATANABE, S.; CHEN, Z.; MALLIDI, S.; HEŘMANSKÝ, H.; TSAKALIDIS, S.; SCHWARTZ, R.

Original Title

Robust Speech Recognition in Unknown Reverberant and Noisy Conditions

English Title

Robust Speech Recognition in Unknown Reverberant and Noisy Conditions

Type

Paper in proceedings (conference paper)

Original Abstract

In this paper, we describe our work on the ASpIRE (AutomaticSpeech recognition In Reverberant Environments)challenge, which aims to assess the robustness of automaticspeech recognition (ASR) systems. The main characteristic ofthe challenge is developing a high-performance system withoutaccess to matched training and development data. Whilethe evaluation data are recorded with far-field microphones innoisy and reverberant rooms, the training data are telephonespeech and close talking. Our approach to this challengeincludes speech enhancement, neural network methods andacoustic model adaptation, We show that these techniquescan successfully alleviate the performance degradation due tonoisy audio and data mismatch.

English abstract

In this paper, we describe our work on the ASpIRE (AutomaticSpeech recognition In Reverberant Environments)challenge, which aims to assess the robustness of automaticspeech recognition (ASR) systems. The main characteristic ofthe challenge is developing a high-performance system withoutaccess to matched training and development data. Whilethe evaluation data are recorded with far-field microphones innoisy and reverberant rooms, the training data are telephonespeech and close talking. Our approach to this challengeincludes speech enhancement, neural network methods andacoustic model adaptation, We show that these techniquescan successfully alleviate the performance degradation due tonoisy audio and data mismatch.

Keywords

ASpIRE challenge, robust speech recognition

Key words in English

ASpIRE challenge, robust speech recognition

Authors

HSIAO, R.; MA, J.; HARTMANN, W.; KARAFIÁT, M.; GRÉZL, F.; BURGET, L.; SZŐKE, I.; ČERNOCKÝ, J.; WATANABE, S.; CHEN, Z.; MALLIDI, S.; HEŘMANSKÝ, H.; TSAKALIDIS, S.; SCHWARTZ, R.

RIV year

2016

Released

13.12.2015

Publisher

IEEE Signal Processing Society

Location

Scottsdale, Arizona

ISBN

978-1-4799-7291-3

Book

Proceedings of 2015 IEEE Automatic Speech Recognition and Understanding Workshop

Pages from

533

Pages to

538

Pages count

6

URL

https://www.fit.vut.cz/research/publication/11067/

BibTex

@inproceedings{BUT120392,
  author="Roger {Hsiao} and Jeff {Ma} and William {Hartmann} and Martin {Karafiát} and František {Grézl} and Lukáš {Burget} and Igor {Szőke} and Jan {Černocký} and Shinji {Watanabe} and Zhuo {Chen} and Sri Harish {Mallidi} and Hynek {Heřmanský} and Stavros {Tsakalidis} and Richard {Schwartz}",
  title="Robust Speech Recognition in Unknown Reverberant and Noisy Conditions",
  booktitle="Proceedings of 2015 IEEE Automatic Speech Recognition and Understanding Workshop",
  year="2015",
  pages="533--538",
  publisher="IEEE Signal Processing Society",
  address="Scottsdale, Arizona",
  doi="10.1109/ASRU.2015.7404841",
  isbn="978-1-4799-7291-3",
  url="https://www.fit.vut.cz/research/publication/11067/"
}

Documents

hsiao_asru2015_0000533