Publication detail

Topic identification of spoken documents using unsupervised acoustic unit discovery

KESIRAJU, S. PAPPAGARI, R. ONDEL YANG, L. BURGET, L. DEHAK, N. KHUDANPUR, S. ČERNOCKÝ, J. GANGASHETTY, S.

Original Title

Topic identification of spoken documents using unsupervised acoustic unit discovery

Type

conference paper

Language

English

Original Abstract

This paper investigates the application of unsupervised acoustic unit discovery for topic identification (topic ID) of spoken audio documents. The acoustic unit discovery method is based on a nonparametric Bayesian phone-loop model that segments a speech utterance into phone-like categories. The discovered phone-like (acoustic) units are further fed into the conventional topic ID framework. Using multilingual bottleneck features for the acoustic unit discovery, we show that the proposed method outperforms other systems that are based on cross-lingual phoneme recognizer.

Keywords

topic identification, acoustic unit discovery, unsupervised learning, non-parametric Bayesian models

Authors

KESIRAJU, S.; PAPPAGARI, R.; ONDEL YANG, L.; BURGET, L.; DEHAK, N.; KHUDANPUR, S.; ČERNOCKÝ, J.; GANGASHETTY, S.

Released

5. 3. 2017

Publisher

IEEE Signal Processing Society

Location

New Orleans

ISBN

978-1-5090-4117-6

Book

Proceedings of ICASSP 2017

Pages from

5745

Pages to

5749

Pages count

5

URL

https://www.fit.vut.cz/research/publication/11470/

BibTex

@inproceedings{BUT144450,
  author="Santosh {Kesiraju} and Raghavendra {Pappagari} and Lucas Antoine Francois {Ondel} and Lukáš {Burget} and Najim {Dehak} and Sanjeev {Khudanpur} and Jan {Černocký} and Suryakanth V {Gangashetty}",
  title="Topic identification of spoken documents using unsupervised acoustic unit discovery",
  booktitle="Proceedings of ICASSP 2017",
  year="2017",
  pages="5745--5749",
  publisher="IEEE Signal Processing Society",
  address="New Orleans",
  doi="10.1109/ICASSP.2017.7953257",
  isbn="978-1-5090-4117-6",
  url="https://www.fit.vut.cz/research/publication/11470/"
}

Documents

kesiraju_icassp2017_0005745.pdf