wav2vec2-based Speech Rating System for Children with Speech Sound Disorder

Yaroslav Getman, Ragheb Al-Ghezi, Ekaterina Voskoboinik, Tamás Grósz, Mikko Kurimo, Giampiero Salvi, Torbjørn Svendsen, Sofia Strömbergsson

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference contributionScientificvertaisarvioitu

95 Lataukset (Pure)

Abstrakti

Speaking is a fundamental way of communication, developed at a young age. Unfortunately, some children with speech sound disorder struggle to acquire this skill, hindering their ability to communicate efficiently. Speech therapies, which could aid these children in speech acquisition, greatly rely on speech practice trials and accurate feedback about their pronunciations. To enable home therapy and lessen the burden on speech-language pathologists, we need a highly accurate and automatic way of assessing the quality of speech uttered by young children. Our work focuses on exploring the applicability of state-of-the-art self-supervised, deep acoustic models, mainly wav2vec2, for this task. The empirical results highlight that these self-supervised models are superior to traditional approaches and close the gap between machine and human performance.
AlkuperäiskieliEnglanti
OtsikkoProceedings of Interspeech'22
KustantajaInternational Speech Communication Association
Sivut3618-3622
Sivumäärä5
DOI - pysyväislinkit
TilaJulkaistu - 2022
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisuussa
TapahtumaInterspeech - Incheon, Etelä-Korea
Kesto: 18 syysk. 202222 syysk. 2022

Julkaisusarja

NimiProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
KustantajaInternational Speech Communication Association
ISSN (painettu)2308-457X
ISSN (elektroninen)1990-9772

Conference

ConferenceInterspeech
Maa/AlueEtelä-Korea
KaupunkiIncheon
Ajanjakso18/09/202222/09/2022

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