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Found 6 papers, 4 papers with code
Comparison of L2 Korean pronunciation error patterns from five L1 backgrounds by using automatic phonetic transcription
This paper presents a large-scale analysis of L2 Korean pronunciation error patterns from five different language backgrounds, Chinese, Vietnamese, Japanese, Thai, and English, by using automatic phonetic transcription.
Speech Intelligibility Assessment of Dysarthric Speech by using Goodness of Pronunciation with Uncertainty Quantification
This paper proposes an improved Goodness of Pronunciation (GoP) that utilizes Uncertainty Quantification (UQ) for automatic speech intelligibility assessment for dysarthric speech.
Automatic Severity Classification of Dysarthric speech by using Self-supervised Model with Multi-task Learning
To tackle the problem, we propose a novel automatic severity assessment method for dysarthric speech, using the self-supervised model in conjunction with multi-task learning.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Opening the Black Box of wav2vec Feature Encoder
Self-supervised models, namely, wav2vec and its variants, have shown promising results in various downstream tasks in the speech domain.
Multilingual analysis of intelligibility classification using English, Korean, and Tamil dysarthric speech datasets
As multilingual analysis, examination on the mean values of acoustic measurements by intelligibility levels is conducted.
Cross-lingual Dysarthria Severity Classification for English, Korean, and Tamil
In order to validate the effectiveness of our proposed method, two baseline experiments are conducted: experiments using the intersection set of mono-lingual feature sets (Intersection) and experiments using the union set of mono-lingual feature sets (Union).
