Detail publikace

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.

Originální název

Topic identification of spoken documents using unsupervised acoustic unit discovery

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

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

Autoři

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

Vydáno

5. 3. 2017

Nakladatel

IEEE Signal Processing Society

Místo

New Orleans

ISBN

978-1-5090-4117-6

Kniha

Proceedings of ICASSP 2017

Strany od

5745

Strany do

5749

Strany počet

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/"
}

Dokumenty

kesiraju_icassp2017_0005745.pdf