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Found 11 papers, 3 papers with code
Speech Corpus for Korean Children with Autism Spectrum Disorder: Towards Automatic Assessment Systems
Despite the growing demand for digital therapeutics for children with Autism Spectrum Disorder (ASD), there is currently no speech corpus available for Korean children with ASD.
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.
A speech corpus for chronic kidney disease
In this study, we present a speech corpus of patients with chronic kidney disease (CKD) that will be used for research on pathological voice analysis, automatic illness identification, and severity prediction.
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
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).
Improving Dysarthric Speech Intelligibility Using Cycle-consistent Adversarial Training
Dysarthria is a motor speech impairment affecting millions of people.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Self-imitating Feedback Generation Using GAN for Computer-Assisted Pronunciation Training
Trained on 97, 200 spectrogram images of short utterances produced by native and non-native speakers of Korean, the generator is able to successfully transform the non-native spectrogram input to a spectrogram with properties of self-imitating feedback.
Dysarthric Speech Database for Development of QoLT Software Technology
This paper also introduces the prompting items, the assessment of the speech disability severity of the speakers, and other considerations for the creation of a dysarthric speech.
Korean Children's Spoken English Corpus and an Analysis of its Pronunciation Variability
This paper introduces a corpus of Korean-accented English speech produced by children (the Korean Children's Spoken English Corpus: the KC-SEC), which is constructed by Seoul National University.
