Weakly supervised spoken term discovery using cross-lingual side information

Sameer Bansal, Herman Kamper, Sharon Goldwater, Adam Lopez

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

Recent work on unsupervised term discovery (UTD) aims to identify and cluster repeated word-like units from audio alone. These systems are promising for some very low-resource languages where transcribed audio is unavailable, or where no written form of the language exists. However, in some cases it may still be feasible (e.g., through crowdsourcing) to obtain (possibly noisy) text translations of the audio. If so, this information could be used as a source of side information to improve UTD. Here, we present a simple method for rescoring the output of a UTD system using text translations, and test it on a corpus of Spanish audio with English translations. We show that it greatly improves the average precision of the results over a wide range of system configurations and data preprocessing methods.
Original languageEnglish
Title of host publicationThe 42nd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2017)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages5760-5764
Number of pages5
ISBN (Electronic)978-1-5090-4117-6
DOIs
Publication statusPublished - 19 Jun 2017
Event42nd IEEE International Conference on Acoustics, Speech and Signal Processing - New Orleans, United States
Duration: 5 Mar 20179 Mar 2017
http://www.ieee-icassp2017.org/

Publication series

Name
PublisherIEEE
ISSN (Electronic)2379-190X

Conference

Conference42nd IEEE International Conference on Acoustics, Speech and Signal Processing
Abbreviated titleICASSP 2017
Country/TerritoryUnited States
CityNew Orleans
Period5/03/179/03/17
Internet address

Fingerprint

Dive into the research topics of 'Weakly supervised spoken term discovery using cross-lingual side information'. Together they form a unique fingerprint.

Cite this