Kei Hashimoto

Kei Hashimoto

Nagoya Institute of Technology

H-index: 17

Asia-Japan

About Kei Hashimoto

Kei Hashimoto, With an exceptional h-index of 17 and a recent h-index of 14 (since 2020), a distinguished researcher at Nagoya Institute of Technology, specializes in the field of Speech synthesis, Speech recognition.

His recent articles reflect a diverse array of research interests and contributions to the field:

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

Embedding a differentiable mel-cepstral synthesis filter to a neural speech synthesis system

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

Singing voice synthesis based on a frame-driven attention mechanism considering vocal timing deviation

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

Autoregressive variational autoencoder with a hidden semi-markov model-based structured attention for speech synthesis

A study on vocal timing modeling for sequence-to-sequence singing voice synthesis

深層ニューラルネットワークに基づく歌声合成のための音響・波形モデリング

Kei Hashimoto Information

University

Position

___

Citations(all)

934

Citations(since 2020)

609

Cited By

530

hIndex(all)

17

hIndex(since 2020)

14

i10Index(all)

28

i10Index(since 2020)

19

Email

University Profile Page

Nagoya Institute of Technology

Google Scholar

View Google Scholar Profile

Kei Hashimoto Skills & Research Interests

Speech synthesis

Speech recognition

Top articles of Kei Hashimoto

Title

Journal

Author(s)

Publication Date

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

arXiv preprint arXiv:2402.14692

Yukiya Hono

Kei Hashimoto

Yoshihiko Nankaku

Keiichi Tokuda

2024/2/22

Embedding a differentiable mel-cepstral synthesis filter to a neural speech synthesis system

Takenori Yoshimura

Shinji Takaki

Kazuhiro Nakamura

Keiichiro Oura

Yukiya Hono

...

2023/6/4

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

Yukiya Hono

Kei Hashimoto

Yoshihiko Nankaku

Keiichi Tokuda

2023/6/4

Singing voice synthesis based on a frame-driven attention mechanism considering vocal timing deviation

IEICE Technical Report; IEICE Tech. Rep.

Miku Nishihara

Yukiya Hono

Kei Hashimoto

Yoshihiko Nankaku

Keiichi Tokuda

2023/2/21

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

arXiv preprint arXiv:2301.02262

Miku Nishihara

Yukiya Hono

Kei Hashimoto

Yoshihiko Nankaku

Keiichi Tokuda

2023/1/5

Autoregressive variational autoencoder with a hidden semi-markov model-based structured attention for speech synthesis

Takato Fujimoto

Kei Hashimoto

Yoshihiko Nankaku

Keiichi Tokuda

2022/5/23

A study on vocal timing modeling for sequence-to-sequence singing voice synthesis

日本音響学会研究発表会講演論文集 (CD-ROM)

MIKU NISHIHARA

YUKIYA HONO

KEI HASHIMOTO

YOSHIHIKO NANKAKU

KEIICHI TOKUDA

2022

深層ニューラルネットワークに基づく歌声合成のための音響・波形モデリング

Yukiya Hono

Yoshihiko NANKAKU

Kei HASHIMOTO

2022/1

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

Yukiya Hono

Shinji Takaki

Kei Hashimoto

Keiichiro Oura

Yoshihiko Nankaku

...

2021/6/6

Sequence-to-sequence speech synthesis using a hidden semi-Markov model based structured attention mechanism.

日本音響学会研究発表会講演論文集 (CD-ROM)

KENTA SUMIYA

TAKENORI YOSHIMURA

SHINJI TAKAKI

KEI HASHIMOTO

KEIICHIRO OURA

...

2021

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

IEEE Access

Yukiya Hono

Shinji Takaki

Kei Hashimoto

Keiichiro Oura

Yoshihiko Nankaku

...

2021/10/5

Neural sequence-to-sequence speech synthesis using a hidden semi-Markov model based structured attention mechanism

arXiv preprint arXiv:2108.13985

Yoshihiko Nankaku

Kenta Sumiya

Takenori Yoshimura

Shinji Takaki

Kei Hashimoto

...

2021/8/31

Sinsy: A deep neural network-based singing voice synthesis system

IEEE/ACM Transactions on Audio, Speech, and Language Processing

Yukiya Hono

Kei Hashimoto

Keiichiro Oura

Yoshihiko Nankaku

Keiichi Tokuda

2021/8/11

Expressive speech synthesis using hierarchical multi-grained generative model

日本音響学会研究発表会講演論文集 (CD-ROM)

YUKIYA HONO

KAZUNA TSUBOI

KEI SAWADA

KEI HASHIMOTO

KEIICHIRO OURA

...

2020

Hierarchical multi-grained generative model for expressive speech synthesis

arXiv preprint arXiv:2009.08474

Yukiya Hono

Kazuna Tsuboi

Kei Sawada

Kei Hashimoto

Keiichiro Oura

...

2020/9/17

Semi-supervised learning based on hierarchical generative models for end-to-end speech synthesis

Takato Fujimoto

Shinji Takaki

Kei Hashimoto

Keiichiro Oura

Yoshihiko Nankaku

...

2020/5/4

Fast and high-quality singing voice synthesis system based on convolutional neural networks

Kazuhiro Nakamura

Shinji Takaki

Kei Hashimoto

Keiichiro Oura

Yoshihiko Nankaku

...

2020/5/4

See List of Professors in Kei Hashimoto University(Nagoya Institute of Technology)