5 accepted papers
This paper presents a novel multilingual speech translation corpus for complex, domain-specific content in Korean, English, Spanish, and Japanese. The corpus contains 4,000 hours of parallel speech, including 1,000 hours of Korean audio with simultaneous sight interpretations in the other three lang…
Although substantial research has been conducted on automatic speech assessment models leveraging speech representations derived from self-supervised learning models, the underlying mechanisms remain relatively underexplored. This study investigates the acoustic foundations of automatic speech produ…
Multilingual L2 speech corpora for developing automatic speech assessment are currently available, but they lack comprehensive annotations of L2 speech from non-native speakers of various languages. This study introduces the methodology of designing a Korean learners’ L2 speech corpus of seven langu…
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. This paper introduces a speech corpus specifically designed for Korean children with ASD, aiming to advance speech technol…
Automatic assessment of dysarthric speech is essential for sustained treatments and rehabilitation. However, obtaining atypical speech is challenging, often leading to data scarcity issues. To tackle the problem, we propose a novel automatic severity assessment method for dysarthric speech, using th…