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

35 citations · 68 across the 6 of their papers we have counts for

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8 papers · 1 filter

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.AS20231 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.AS20221 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.AS20214 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…

eess.AS202135 cited

Sinsy: A Deep Neural Network-Based Singing Voice Synthesis System

Yukiya Hono, Kei Hashimoto, Keiichiro Oura +2

This paper presents Sinsy, a deep neural network (DNN)-based singing voice synthesis (SVS) system. In recent years, DNNs have been utilized in statistical parametric SVS systems, a…

eess.AS20211 cited

PeriodNet: A non-autoregressive waveform generation model with a structure separating periodic and aperiodic components

Yukiya Hono, Shinji Takaki, Kei Hashimoto +3

We propose PeriodNet, a non-autoregressive (non-AR) waveform generation model with a new model structure for modeling periodic and aperiodic components in speech waveforms. The non…