We present the JVNV, a Japanese emotional speech corpus with verbal content and
nonverbal vocalizations whose scripts are generated by a large-scale language model …

Large language models (LLMs) are being adopted in a wide range of applications, but an
understanding of other social-affective signals is needed to support effective human …

In recent years, advancements in the field of speech processing have led to cutting-edge
deep learning algorithms with immense potential for real-world applications. The automated …

Understanding human emotions is paramount for effective human-human interactions. As
technology advances, social robots are increasingly being developed with the capability to …

In this study, we investigate multimodal foundation models (MFMs) for emotion recognition
from non-verbal sounds. We hypothesize that MFMs, with their joint pre-training across …

Face-to-face communication modeling in computer vision is an area of research focusing on
developing algorithms that can recognize and analyze non-verbal cues and behaviors …

The pronunciation quality of second language (L2) learners can be affected by different
factors including the following seven factors: Intelligibility, Intonation, Phoneme quality …

Speech intelligibility is crucial in language learning for effective communication. Thus, to
develop computer-assisted language learning systems, automatic speech intelligibility …

This thesis explores the critical challenges and provides solutions associated with automatic
spoken data validation in the complex multilingual and multicultural context of India, which is …