Transparent pronunciation scoring using articulatorily weighted phoneme edit distance

Reima Karhila, Anna Riikka Smolander, Sari Ylinen, Mikko Kurimo

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

2 Citations (Scopus)
94 Downloads (Pure)

Abstract

For researching effects of gamification in foreign language learning for children in the “Say It Again, Kid!” project we developed a feedback paradigm that can drive gameplay in pronunciation learning games. We describe our scoring system based on the difference between a reference phone sequence and the output of a multilingual CTC phoneme recogniser. We present a white-box scoring model of mapped weighted Levenshtein edit distance between reference and error with error weights for articulatory differences computed from a training set of scored utterances. The system can produce a human-readable list of each detected mispronunciation's contribution to the utterance score. We compare our scoring method to established black box methods.

Original languageEnglish
Title of host publicationProceedings of Interspeech
PublisherInternational Speech Communication Association
Pages1866-1870
Number of pages5
Volume2019-September
DOIs
Publication statusPublished - 1 Jan 2019
MoE publication typeA4 Article in a conference publication
EventInterspeech - Graz, Austria
Duration: 15 Sep 201919 Sep 2019
https://www.interspeech2019.org/

Publication series

NameInterspeech - Annual Conference of the International Speech Communication Association
ISSN (Electronic)2308-457X

Conference

ConferenceInterspeech
CountryAustria
CityGraz
Period15/09/201919/09/2019
Internet address

Keywords

  • Computer Assisted Pronunciation Training
  • Mispronunciation Detection
  • Multilingual Phoneme Recognition

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