35 citations · 44 across the 14 of their papers we have counts for
9 papers · 1 filter
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,…
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…
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…
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…
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…
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…
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…
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…
Hierarchical Multi-Grained Generative Model for Expressive Speech Synthesis
Yukiya Hono, Kazuna Tsuboi, Kei Sawada +4
This paper proposes a hierarchical generative model with a multi-grained latent variable to synthesize expressive speech. In recent years, fine-grained latent variables are introdu…