activity
20192024
most citedSinsy: A Deep Neural Network-Based Singing Voice Synthesis System

35 citations · 72 across the 10 of their papers we have counts for

collaborators

11 papers

eess.AS2024

PeriodGrad: Towards Pitch-Controllable Neural Vocoder Based on a Diffusion Probabilistic Model

Yukiya Hono, Kei Hashimoto, Yoshihiko Nankaku +1

This paper presents a neural vocoder based on a denoising diffusion probabilistic model (DDPM) incorporating explicit periodic signals as auxiliary conditioning signals. Recently,…

eess.AS2023★ 1 cited

Singing voice synthesis based on frame-level sequence-to-sequence models considering vocal timing deviation

Miku Nishihara, Yukiya Hono, Kei Hashimoto +2

This paper proposes singing voice synthesis (SVS) based on frame-level sequence-to-sequence models considering vocal timing deviation. In SVS, it is essential to synchronize the ti…

eess.AS2022★ 1 cited

Singing Voice Synthesis Based on a Musical Note Position-Aware Attention Mechanism

Yukiya Hono, Kei Hashimoto, Yoshihiko Nankaku +1

This paper proposes a novel sequence-to-sequence (seq2seq) model with a musical note position-aware attention mechanism for singing voice synthesis (SVS). A seq2seq modeling approa…

eess.AS2022★ 1 cited

Embedding a Differentiable Mel-cepstral Synthesis Filter to a Neural Speech Synthesis System

Takenori Yoshimura, Shinji Takaki, Kazuhiro Nakamura +5

This paper integrates a classic mel-cepstral synthesis filter into a modern neural speech synthesis system towards end-to-end controllable speech synthesis. Since the mel-cepstral…

eess.AS2022

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…

eess.AS2021★ 4 cited

Neural Sequence-to-Sequence Speech Synthesis Using a Hidden Semi-Markov Model Based Structured Attention Mechanism

Yoshihiko Nankaku, Kenta Sumiya, Takenori Yoshimura +4

This paper proposes a novel Sequence-to-Sequence (Seq2Seq) model integrating the structure of Hidden Semi-Markov Models (HSMMs) into its attention mechanism. In speech synthesis, i…