Publication Details

Automatic Speech Recognition and Topic Identification for Almost-Zero-Resource Languages

WIESNER, M.; LIU, C.; ONDEL YANG, L.; HARMAN, C.; MANOHAR, V.; TRMAL, J.; HUANG, Z.; DEHAK, N.; KHUDANPUR, S. Automatic Speech Recognition and Topic Identification for Almost-Zero-Resource Languages. In Proceedings of Interspeech. Proceedings of Interspeech. Hyderabad: International Speech Communication Association, 2018. p. 2052-2056. ISSN: 1990-9772.
Czech title
Automatické rozpoznávání řeči a identifikace témat pro jazyky s téměř neexistujícími zdroji
Type
conference paper
Language
English
Authors
Wiesner Matthew (FIT)
Liu Chunxi (FIT)
ONDEL YANG, L.
HARMAN, C.
MANOHAR, V.
Trmal Jan, Ing., Ph.D.
HUANG, Z.
Dehak Najim
Khudanpur Sanjeev
URL
Keywords

Universal acoustic models, topic identification, cross-language information retrieval, transfer learning, lowresource speech recognition

Abstract

Automatic speech recognition (ASR) systems often need to be developed for extremely low-resource languages to serve enduses such as audio content categorization and search. While universal phone recognition is natural to consider when no transcribed speech is available to train an ASR system in a language, adapting universal phone models using very small amounts (minutes rather than hours) of transcribed speech also needs to be studied, particularly with state-of-the-art DNN-based acoustic models. The DARPA LORELEI program provides a framework for such very-low-resource ASR studies, and provides an extrinsic metric for evaluating ASR performance in a humanitarian assistance, disaster relief setting. This paper presents our Kaldi-based systems for the program, which employ a universal phone modeling approach to ASR, and describes recipes for very rapid adaptation of this universal ASR system. The results we obtain significantly outperform results obtained by many competing approaches on the NIST LoReHLT 2017 Evaluation datasets

Published
2018
Pages
2052–2056
Journal
Proceedings of Interspeech, vol. 2018, no. 9, ISSN 1990-9772
Proceedings
Proceedings of Interspeech
Publisher
International Speech Communication Association
Place
Hyderabad
DOI
UT WoS
000465363900431
EID Scopus
BibTeX
@inproceedings{BUT163405,
  author="WIESNER, M. and LIU, C. and ONDEL YANG, L. and HARMAN, C. and MANOHAR, V. and TRMAL, J. and HUANG, Z. and DEHAK, N. and KHUDANPUR, S.",
  title="Automatic Speech Recognition and Topic Identification for Almost-Zero-Resource Languages",
  booktitle="Proceedings of Interspeech",
  year="2018",
  journal="Proceedings of Interspeech",
  volume="2018",
  number="9",
  pages="2052--2056",
  publisher="International Speech Communication Association",
  address="Hyderabad",
  doi="10.21437/Interspeech.2018-1836",
  issn="1990-9772",
  url="https://www.isca-speech.org/archive/Interspeech_2018/abstracts/1836.html"
}
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