Accents pose significant challenges for speech recognition systems. Although joint
automatic speech recognition (ASR) and accent recognition (AR) training has been proven …

State-of-the-art automatic speech recognition models often struggle to capture nuanced
features inherent in accented speech, leading to sub-optimal performance in speaker …

Recent studies on pronunciation scoring have explored the effect of introducing phone
embeddings as reference pronunciation, but mostly in an implicit manner, ie, addition or …

Accurate recognition of human intent is crucial for effective human–computer speech
interaction. Numerous intent understanding studies were based on speech-to-text …

The inherent variability in pronunciation across different accents presents a significant
challenge to accurate speech recognition, greatly impairing the performance of current end …

Accent recognition (AR) is challenging due to the lack of training data as well as the accents
are entangled with speakers and regional characteristics. This paper aims to improve AR …

Despite notable advancements in automatic speech recognition (ASR), performance tends
to degrade when faced with adverse conditions. Generative error correction (GER) …

Automatic detection and severity assessment of dysarthria are crucial for delivering targeted
therapeutic interventions to patients. While most existing research focuses primarily on …