Detail publikace

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.

Originální název

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

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

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

Klíčová slova

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

Autoři

WIESNER, M.; LIU, C.; ONDEL YANG, L.; HARMAN, C.; MANOHAR, V.; TRMAL, J.; HUANG, Z.; DEHAK, N.; KHUDANPUR, S.

Vydáno

2. 9. 2018

Nakladatel

International Speech Communication Association

Místo

Hyderabad

ISSN

1990-9772

Periodikum

Proceedings of Interspeech

Ročník

2018

Číslo

9

Stát

Francouzská republika

Strany od

2052

Strany do

2056

Strany počet

5

URL

https://www.isca-speech.org/archive/Interspeech_2018/abstracts/1836.html

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"
}

Dokumenty

wiesner_interspeech2018_1836.pdf