41 citations · 47 across the 11 of their papers we have counts for
11 papers
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…
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…
Release of Pre-Trained Models for the Japanese Language
Kei Sawada, Tianyu Zhao, Makoto Shing +5
AI democratization aims to create a world in which the average person can utilize AI techniques. To achieve this goal, numerous research institutes have attempted to make their res…
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…
Towards human-like spoken dialogue generation between AI agents from written dialogue
Kentaro Mitsui, Yukiya Hono, Kei Sawada
The advent of large language models (LLMs) has made it possible to generate natural written dialogues between two agents. However, generating human-like spoken dialogues from these…
Text-Guided Scene Sketch-to-Photo Synthesis
AprilPyone MaungMaung, Makoto Shing, Kentaro Mitsui +2
We propose a method for scene-level sketch-to-photo synthesis with text guidance. Although object-level sketch-to-photo synthesis has been widely studied, whole-scene synthesis is…
UniFLG: Unified Facial Landmark Generator from Text or Speech
Kentaro Mitsui, Yukiya Hono, Kei Sawada
Talking face generation has been extensively investigated owing to its wide applicability. The two primary frameworks used for talking face generation comprise a text-driven framew…
End-to-End Text-to-Speech Based on Latent Representation of Speaking Styles Using Spontaneous Dialogue
Kentaro Mitsui, Tianyu Zhao, Kei Sawada +3
The recent text-to-speech (TTS) has achieved quality comparable to that of humans; however, its application in spoken dialogue has not been widely studied. This study aims to reali…
MSR-NV: Neural Vocoder Using Multiple Sampling Rates
Kentaro Mitsui, Kei Sawada
The development of neural vocoders (NVs) has resulted in the high-quality and fast generation of waveforms. However, conventional NVs target a single sampling rate and require re-t…
Multi-speaker Text-to-speech Synthesis Using Deep Gaussian Processes
Kentaro Mitsui, Tomoki Koriyama, Hiroshi Saruwatari
Multi-speaker speech synthesis is a technique for modeling multiple speakers' voices with a single model. Although many approaches using deep neural networks (DNNs) have been propo…
JVS corpus: free Japanese multi-speaker voice corpus
Shinnosuke Takamichi, Kentaro Mitsui, Yuki Saito +3
Thanks to improvements in machine learning techniques, including deep learning, speech synthesis is becoming a machine learning task. To accelerate speech synthesis research, we ar…