Fine-Tuning Self-Supervised Learning Models for End-to-End Pronunciation Scoring

Automatic pronunciation assessment models are regularly used in language learning applications. Common methodologies for pronunciation assessment use feature-based approaches, such as the Goodness-of-Pronunciation (GOP) approach, or deep learning speech recognition models to perform speech assessmen...

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Hlavní autoři:	Ahmed I. Zahran, Aly A. Fahmy, Khaled T. Wassif, Hanaa Bayomi
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	IEEE 2023-01-01
Edice:	IEEE Access
Témata:	Automatic pronunciation assessment pronunciation scoring pre-trained speech representations self-supervised speech representation learning wav2vec 20 WavLM
On-line přístup:	https://ieeexplore.ieee.org/document/10255657/
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Fine-Tuning Self-Supervised Learning Models for End-to-End Pronunciation Scoring

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