Detail publikace

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.

Originální název

Robust Speech Recognition in Unknown Reverberant and Noisy Conditions

Anglický název

Robust Speech Recognition in Unknown Reverberant and Noisy Conditions

Jazyk

en

Originální abstrakt

In this paper, we describe our work in the ASpIRE challenge. We experiment and evaluate different approaches to tackling the performance degradation due to noise and data mismatch. Our approaches include audio enhancement, data augmentation, unsupervised DNN adaptation, and system combination.

Anglický abstrakt

In this paper, we describe our work in the ASpIRE challenge. We experiment and evaluate different approaches to tackling the performance degradation due to noise and data mismatch. Our approaches include audio enhancement, data augmentation, unsupervised DNN adaptation, and system combination.

Dokumenty

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",
  annote="In this paper, we describe our work in the ASpIRE challenge. We experiment and
evaluate different approaches to tackling the performance degradation due to
noise and data mismatch. Our approaches include audio enhancement, data
augmentation, unsupervised DNN adaptation, and system combination.",
  address="IEEE Signal Processing Society",
  booktitle="Proceedings of 2015 IEEE Automatic Speech Recognition and Understanding Workshop",
  chapter="120392",
  doi="10.1109/ASRU.2015.7404841",
  edition="NEUVEDEN",
  howpublished="electronic, physical medium",
  institution="IEEE Signal Processing Society",
  year="2015",
  month="december",
  pages="533--538",
  publisher="IEEE Signal Processing Society",
  type="conference paper"
}