Massively multilingual adversarial speech recognition

Oliver Adams, Matthew Wiesner, Shinji Watanabe, David Yarowsky

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

1 Citation (Scopus)

Abstract

We report on adaptation of multilingual end-to-end speech recognition models trained on as many as 100 languages. Our findings shed light on the relative importance of similarity between the target and pretraining languages along the dimensions of phonetics, phonology, language family, geographical location, and orthography. In this context, experiments demonstrate the effectiveness of two additional pretraining objectives in encouraging language-independent encoder representations: a context-independent phoneme objective paired with a language-adversarial classification objective.

Original languageEnglish
Title of host publicationLong and Short Papers
PublisherAssociation for Computational Linguistics (ACL)
Pages96-108
Number of pages13
ISBN (Electronic)9781950737130
Publication statusPublished - 2019
Externally publishedYes
Event2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2019 - Minneapolis, United States
Duration: 2019 Jun 22019 Jun 7

Publication series

NameNAACL HLT 2019 - 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Proceedings of the Conference
Volume1

Conference

Conference2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2019
CountryUnited States
CityMinneapolis
Period19/6/219/6/7

ASJC Scopus subject areas

  • Language and Linguistics
  • Computer Science Applications
  • Linguistics and Language

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  • Cite this

    Adams, O., Wiesner, M., Watanabe, S., & Yarowsky, D. (2019). Massively multilingual adversarial speech recognition. In Long and Short Papers (pp. 96-108). (NAACL HLT 2019 - 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Proceedings of the Conference; Vol. 1). Association for Computational Linguistics (ACL).