3 papers
eess.AS2026
PASQA: Pitch-Accent-Focused Speech Quality Assessment Model Trained on Synthetic Speech with Accent Errors
Masaya Kawamura, Yuma Shirahata, Kentaro Mitsui +1
Existing mean opinion score (MOS) prediction models typically predict utterance-level naturalness MOS and can be insensitive to localized pitch-accent errors. We propose Pitch-Acce…
cs.CL2024
PSLM: Parallel Generation of Text and Speech with LLMs for Low-Latency Spoken Dialogue Systems
Kentaro Mitsui, Koh Mitsuda, Toshiaki Wakatsuki +2
Multimodal language models that process both text and speech have a potential for applications in spoken dialogue systems. However, current models face two major challenges in resp…
eess.AS2024
Integrating Pre-Trained Speech and Language Models for End-to-End Speech Recognition
Yukiya Hono, Koh Mitsuda, Tianyu Zhao +3
Advances in machine learning have made it possible to perform various text and speech processing tasks, such as automatic speech recognition (ASR), in an end-to-end (E2E) manner. E…