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Chapter

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Title

Aaron Earned an Iron Urn: Speech-to-IPA Models Improve Diagnostic of Pronunciation

Authors

[ 1 ] Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | [ 2 ] Instytut Informatyki, Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | [ S ] student | [ SzD ] doctoral school student | [ P ] employee

Scientific discipline (Law 2.0)

[2.3] Information and communication technology

Year of publication

2023

Chapter type

chapter in monograph / paper

Publication language

english

Keywords
EN
  • Wav2Vec
  • IPA
  • pronunciation diagnostic
  • ASR
Abstract

EN Learning the proper pronunciation is one of the key aspects of foreign language acquisition. Assessment of the correctness of pronunciation requires the involvement of expert phoneticians and linguists, severely limiting the scalability of learning solutions. However, the recent adaptation of the Transformer architecture to the audio domain opens the way for automatic model-based assessment of pronunciation. In this paper, we present the pronunciation diagnostic tool developed at PUT and we experimentally evaluate the correlation between expert human assessment and automatic model assessment. By combining the Wav2Vec model and the IPA representation, we prove that pronunciation assessment can be performed automatically with high precision.

Pages (from - to)

273 - 279

DOI

10.34658/9788366741928.43

URL

https://repozytorium.p.lodz.pl/items/6d6df3ee-f3cd-46f5-b3f3-a1525e203715

Book

Progress in Polish Artificial Intelligence Research 4

Presented on

4th Polish Conference on Artificial Intelligence PP-RAI'2023, 24-26.04.2023, Łódź, Polska

License type

dla wszystkich w zakresie dozwolonego użytku

Open Access Mode

open repository

Open Access Text Version

final published version

Date of Open Access to the publication

at the time of publication

Ministry points / chapter

20

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