Publication detail

BUT OpenSAT 2017 speech recognition system

KARAFIÁT, M. BASKAR, M. SZŐKE, I. MALENOVSKÝ, V. VESELÝ, K. GRÉZL, F. BURGET, L. ČERNOCKÝ, J.

Original Title

BUT OpenSAT 2017 speech recognition system

Type

conference paper

Language

English

Original Abstract

(ASR) systems for two domains in OpenSAT evaluations: Low Resourced Languages and Public Safety Communications. The first was challenging due to lack of training data, therefore multilingual approaches for BLSTM training were employed and recently published Residual Memory Networks requiring less training data were used. Combination of both approaches led to superior performance. The second domain was challenging due to recording in extreme conditions: specific channel, speaker under stress, high levels of noise. A data augmentation process was very important to get reasonably good performance.

Keywords

speech recognition, multilingual training, BLSTM, data augmentation, robustness

Authors

KARAFIÁT, M.; BASKAR, M.; SZŐKE, I.; MALENOVSKÝ, V.; VESELÝ, K.; GRÉZL, F.; BURGET, L.; ČERNOCKÝ, J.

Released

2. 9. 2018

Publisher

International Speech Communication Association

Location

Hyderabad

ISBN

1990-9772

Periodical

Proceedings of Interspeech

Year of study

2018

Number

9

State

French Republic

Pages from

2638

Pages to

2642

Pages count

5

URL

BibTex

@inproceedings{BUT155099,
  author="Martin {Karafiát} and Murali Karthick {Baskar} and Igor {Szőke} and Vladimír {Malenovský} and Karel {Veselý} and František {Grézl} and Lukáš {Burget} and Jan {Černocký}",
  title="BUT OpenSAT 2017 speech recognition system",
  booktitle="Proceedings of Interspeech 2018",
  year="2018",
  journal="Proceedings of Interspeech",
  volume="2018",
  number="9",
  pages="2638--2642",
  publisher="International Speech Communication Association",
  address="Hyderabad",
  doi="10.21437/Interspeech.2018-2457",
  issn="1990-9772",
  url="https://www.isca-speech.org/archive/Interspeech_2018/abstracts/2457.html"
}