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Kei Hashimoto
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2020 – today
- 2024
- [c62]Yukiya Hono, Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda:
PeriodGrad: Towards Pitch-Controllable Neural Vocoder Based on a Diffusion Probabilistic Model. ICASSP 2024: 12782-12786 - [i9]Yukiya Hono, Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda:
PeriodGrad: Towards Pitch-Controllable Neural Vocoder Based on a Diffusion Probabilistic Model. CoRR abs/2402.14692 (2024) - 2023
- [c61]Yukiya Hono, Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda:
Singing Voice Synthesis Based on a Musical Note Position-Aware Attention Mechanism. ICASSP 2023: 1-5 - [c60]Takenori Yoshimura, Shinji Takaki, Kazuhiro Nakamura, Keiichiro Oura, Yukiya Hono, Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda:
Embedding a Differentiable Mel-Cepstral Synthesis Filter to a Neural Speech Synthesis System. ICASSP 2023: 1-5 - [i8]Miku Nishihara, Yukiya Hono, Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda:
Singing voice synthesis based on frame-level sequence-to-sequence models considering vocal timing deviation. CoRR abs/2301.02262 (2023) - 2022
- [c59]Takato Fujimoto, Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda:
Autoregressive Variational Autoencoder with a Hidden Semi-Markov Model-Based Structured Attention for Speech Synthesis. ICASSP 2022: 7462-7466 - [i7]Takenori Yoshimura, Shinji Takaki, Kazuhiro Nakamura, Keiichiro Oura, Yukiya Hono, Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda:
Embedding a Differentiable Mel-cepstral Synthesis Filter to a Neural Speech Synthesis System. CoRR abs/2211.11222 (2022) - [i6]Yukiya Hono, Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda:
Singing Voice Synthesis Based on a Musical Note Position-Aware Attention Mechanism. CoRR abs/2212.13703 (2022) - 2021
- [j10]Yukiya Hono
, Shinji Takaki
PeriodNet: A Non-Autoregressive Raw Waveform Generative Model With a Structure Separating Periodic and Aperiodic Components. IEEE Access 9: 137599-137612 (2021) - [j9]Yukiya Hono
Sinsy: A Deep Neural Network-Based Singing Voice Synthesis System. IEEE ACM Trans. Audio Speech Lang. Process. 29: 2803-2815 (2021) - [c58]Yukiya Hono, Shinji Takaki, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
Periodnet: A Non-Autoregressive Waveform Generation Model with a Structure Separating Periodic and Aperiodic Components. ICASSP 2021: 6049-6053 - [i5]Yukiya Hono, Shinji Takaki, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
PeriodNet: A non-autoregressive waveform generation model with a structure separating periodic and aperiodic components. CoRR abs/2102.07786 (2021) - [i4]Yukiya Hono, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
Sinsy: A Deep Neural Network-Based Singing Voice Synthesis System. CoRR abs/2108.02776 (2021) - 2020
- [c57]Kazuhiro Nakamura, Shinji Takaki, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
Fast and High-Quality Singing Voice Synthesis System Based on Convolutional Neural Networks. ICASSP 2020: 7239-7243 - [c56]Takato Fujimoto, Shinji Takaki, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
Semi-Supervised Learning Based on Hierarchical Generative Models for End-to-End Speech Synthesis. ICASSP 2020: 7644-7648 - [c55]Yukiya Hono, Kazuna Tsuboi, Kei Sawada, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
Hierarchical Multi-Grained Generative Model for Expressive Speech Synthesis. INTERSPEECH 2020: 3441-3445 - [i3]Yukiya Hono, Kazuna Tsuboi, Kei Sawada, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
Hierarchical Multi-Grained Generative Model for Expressive Speech Synthesis. CoRR abs/2009.08474 (2020)
2010 – 2019
- 2019
- [c54]Yukiya Hono, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
Singing Voice Synthesis Based on Generative Adversarial Networks. ICASSP 2019: 6955-6959 - [c53]Takenori Yoshimura, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
Speaker-dependent Wavenet-based Delay-free Adpcm Speech Coding. ICASSP 2019: 7145-7149 - [c52]Keiichiro Oura, Kazuhiro Nakamura, Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda:
Deep neural network based real-time speech vocoder with periodic and aperiodic inputs. SSW 2019: 13-18 - [c51]Takato Fujimoto, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
Impacts of input linguistic feature representation on Japanese end-to-end speech synthesis. SSW 2019: 166-171 - [c50]Motoki Shimada, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
Low computational cost speech synthesis based on deep neural networks using hidden semi-Markov model structures. SSW 2019: 177-182 - [i2]Kazuhiro Nakamura, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
Singing voice synthesis based on convolutional neural networks. CoRR abs/1904.06868 (2019) - [i1]Kazuhiro Nakamura, Shinji Takaki, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
Fast and High-Quality Singing Voice Synthesis System based on Convolutional Neural Networks. CoRR abs/1910.11690 (2019) - 2018
- [j8]Takenori Yoshimura
Mel-Cepstrum-Based Quantization Noise Shaping Applied to Neural-Network-Based Speech Waveform Synthesis. IEEE ACM Trans. Audio Speech Lang. Process. 26(7): 1173-1180 (2018) - [c49]Takayuki Kasugai, Yoshinari Tsuzuki, Kei Sawada, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
Image Recognition Based on Convolutional Neural Networks Using Features Generated from Separable Lattice Hidden Markov Models. APSIPA 2018: 324-328 - [c48]Kento Nakao, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
Speaker Adaptation for Speech Synthesis Based on Deep Neural Networks Using Hidden Semi-Markov Model Structures. APSIPA 2018: 638-643 - [c47]Takato Fujimoto, Takenori Yoshimura, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
Speech Synthesis Using WaveNet Vocoder Based on Periodic/Aperiodic Decomposition. APSIPA 2018: 644-648 - [c46]Yukiya Hono, Shumma Murata, Kazuhiro Nakamura, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
Recent Development of the DNN-based Singing Voice Synthesis System - Sinsy. APSIPA 2018: 1003-1009 - [c45]Takenori Yoshimura, Natsumi Koike, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
Discriminative Feature Extraction Based on Sequential Variational Autoencoder for Speaker Recognition. APSIPA 2018: 1742-1746 - [c44]Koki Senda, Yukiya Hono, Kei Sawada, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
Singing Voice Conversion Using Posted Waveform Data on Music Social Media. APSIPA 2018: 1913-1917 - [c43]Kei Sawada, Takenori Yoshimura, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
The NITech text-to-speech system for the Blizzard Challenge 2018. Blizzard Challenge 2018 - [c42]Eiji Ichikawa, Kei Sawada, Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda:
Image Recognition Based on Separable Lattice Hmms Using a Deep Neural Network for Output Probability Distributions. ICASSP 2018: 3021-3025 - [c41]Jumpei Niwa, Takenori Yoshimura, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
Statistical Voice Conversion Based on Wavenet. ICASSP 2018: 5289-5293 - [c40]Takenori Yoshimura, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
WaveNet-Based Zero-Delay Lossless Speech Coding. SLT 2018: 153-158 - 2017
- [j7]Takenori Yoshimura, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
Simultaneous Optimization of Multiple Tree-Based Factor Analyzed HMM for Speech Synthesis. IEEE ACM Trans. Audio Speech Lang. Process. 25(9): 1836-1845 (2017) - [c39]Kei Sawada, Kei Hashimoto, Keiichiro Oura, Keiichi Tokuda:
The NITech text-to-speech system for the Blizzard Challenge 2017. Blizzard Challenge 2017 - [c38]Md. Khayrul Bashar
Analyzing orientation patterns of human skin fibroblasts using image gradient information. EMBC 2017: 600-603 - [c37]Yoshinari Tsuzuki, Kei Sawada, Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda:
Image recognition based on discriminative models using features generated from separable lattice HMMS. ICASSP 2017: 2607-2611 - [c36]Amelia Jane Gully, Takenori Yoshimura, Damian T. Murphy, Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda:
Articulatory Text-to-Speech Synthesis Using the Digital Waveguide Mesh Driven by a Deep Neural Network. INTERSPEECH 2017: 234-238 - [p1]Keiichi Tokuda, Akinobu Lee, Yoshihiko Nankaku, Keiichiro Oura, Kei Hashimoto, Daisuke Yamamoto, Ichi Takumi, Takahiro Uchiya, Shuhei Tsutsumi, Steve Renals
User Generated Dialogue Systems: uDialogue. Human-Harmonized Information Technology (2) 2017: 77-114 - 2016
- [j6]Kei Sawada, Akira Tamamori, Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda:
A Bayesian Approach to Image Recognition Based on Separable Lattice Hidden Markov Models. IEICE Trans. Inf. Syst. 99-D(12): 3119-3131 (2016) - [c35]Kei Sawada, Chiaki Asai, Kei Hashimoto, Keiichiro Oura, Keiichi Tokuda:
The NITech text-to-speech system for the Blizzard Challenge 2016. Blizzard Challenge 2016 - [c34]Kei Hashimoto, Junichi Yamagishi, Isao Echizen:
Privacy-preserving sound to degrade automatic speaker verification performance. ICASSP 2016: 5500-5504 - [c33]Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
Trajectory training considering global variance for speech synthesis based on neural networks. ICASSP 2016: 5600-5604 - [c32]Naoki Hosaka, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
Voice Conversion Based on Trajectory Model Training of Neural Networks Considering Global Variance. INTERSPEECH 2016: 307-311 - [c31]Masanari Nishimura, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
Singing Voice Synthesis Based on Deep Neural Networks. INTERSPEECH 2016: 2478-2482 - [c30]Rasmus Dall, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
Redefining the Linguistic Context Feature Set for HMM and DNN TTS Through Position and Parsing. INTERSPEECH 2016: 2851-2855 - [c29]Keiichi Tokuda, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku:
Temporal modeling in neural network based statistical parametric speech synthesis. SSW 2016: 106-111 - 2015
- [c28]Kei Sawada, Kei Hashimoto, Keiichiro Oura, Keiichi Tokuda:
The NITECH HMM-based text-to-speech system for the Blizzard Challenge 2015. Blizzard Challenge 2015 - [c27]Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
The effect of neural networks in statistical parametric speech synthesis. ICASSP 2015: 4455-4459 - [c26]Takenori Yoshimura, Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda:
Simultaneous optimization of multiple tree structures for factor analyzed HMM-based speech synthesis. INTERSPEECH 2015: 1196-1200 - 2014
- [j5]Kazuhiro Nakamura, Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda:
Integration of Spectral Feature Extraction and Modeling for HMM-Based Speech Synthesis. IEICE Trans. Inf. Syst. 97-D(6): 1438-1448 (2014) - [c25]Kei Sawada, Shinji Takaki, Kei Hashimoto, Keiichiro Oura, Keiichi Tokuda:
Overview of NITECH HMM-based text-to-speech system for Blizzard Challenge 2014. Blizzard Challenge 2014 - [c24]Kanako Shirota, Kazuhiro Nakamura, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
Integration of speaker and pitch adaptive training for HMM-based singing voice synthesis. ICASSP 2014: 2559-2563 - [c23]Kazuhiro Nakamura, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
A mel-cepstral analysis technique restoring high frequency components from low-sampling-rate speech. INTERSPEECH 2014: 2494-2498 - 2013
- [j4]Sayaka Shiota, Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda:
A Bayesian Framework Using Multiple Model Structures for Speech Recognition. IEICE Trans. Inf. Syst. 96-D(4): 939-948 (2013) - [c22]Kei Sawada, Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda:
Image recognition based on hidden Markov eigen-image models using variational Bayesian method. APSIPA 2013: 1-8 - [c21]Shinji Takaki, Kei Sawada, Kei Hashimoto, Keiichiro Oura, Keiichi Tokuda:
Overview of NITECH HMM-based speech synthesis system for Blizzard Challenge 2013. Blizzard Challenge 2013 - [c20]Takaya Makino, Shinji Takaki, Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda:
Separable lattice 2-D HMMS introducing state duration control for recognition of images with various variations. ICASSP 2013: 3203-3207 - [c19]Kazuhiro Nakamura, Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda:
Integration of acoustic modeling and mel-cepstral analysis for HMM-based speech synthesis. ICASSP 2013: 7883-7887 - [c18]Takenori Yoshimura, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
Cross-lingual speaker adaptation based on factor analysis using bilingual speech data for HMM-based speech synthesis. SSW 2013: 297-302 - 2012
- [j3]Kei Hashimoto, Junichi Yamagishi, William Byrne, Simon King
Impacts of machine translation and speech synthesis on speech-to-speech translation. Speech Commun. 54(7): 857-866 (2012) - [c17]Shinji Takaki, Kei Sawada, Kei Hashimoto, Keiichiro Oura, Keiichi Tokuda:
Overview of NIT HMM-based speech synthesis system for Blizzard Challenge 2012. Blizzard Challenge 2012 - [c16]Kei Sawada, Akira Tamamori, Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda:
Face recognition based on separable lattice 2-D HMMS using variational bayesian method. ICASSP 2012: 2205-2208 - [c15]Sayaka Shiota, Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda:
A model structure integration based on a Bayesian framework for speech recognition. ICASSP 2012: 4813-4816 - [c14]Takafumi Hattori, Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda:
A Bayesian Approach to Speaker Recognition Based on GMMs Using Multiple Model Structures. INTERSPEECH 2012: 1107-1110 - 2011
- [j2]Kei Hashimoto, Heiga Zen, Yoshihiko Nankaku, Akinobu Lee, Keiichi Tokuda:
Bayesian Context Clustering Using Cross Validation for Speech Recognition. IEICE Trans. Inf. Syst. 94-D(3): 668-678 (2011) - [c13]Kei Hashimoto, Shinji Takaki, Keiichiro Oura, Keiichi Tokuda:
Overview of NIT HMM-based speech synthesis system for Blizzard Challenge 2011. Blizzard Challenge 2011 - [c12]Kei Hashimoto, Junichi Yamagishi, William J. Byrne, Simon King
An analysis of machine translation and speech synthesis in speech-to-speech translation system. ICASSP 2011: 5108-5111 - [c11]Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda:
Multi-Speaker Modeling with Shared Prior Distributions and Model Structures for Bayesian Speech Synthesis. INTERSPEECH 2011: 113-116 - 2010
- [c10]Keiichiro Oura, Kei Hashimoto, Sayaka Shiota, Keiichi Tokuda:
Overview of NIT HMM-based speech synthesis system for Blizzard Challenge 2010. Blizzard Challenge 2010 - [c9]Pascual Martínez-Gómez, Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda, Germán Sanchis-Trilles:
A Deterministic Annealing-Based Training Algorithm For Statistical Machine Translation Models. EAMT 2010 - [c8]Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda:
Bayesian speech synthesis framework integrating training and synthesis processes. SSW 2010: 106-111
2000 – 2009
- 2009
- [j1]Kei Hashimoto, Hirofumi Yamamoto, Hideo Okuma, Eiichiro Sumita, Keiichi Tokuda:
A Reordering Model Using a Source-Side Parse-Tree for Statistical Machine Translation. IEICE Trans. Inf. Syst. 92-D(12): 2386-2393 (2009) - [c7]Kei Hashimoto, Heiga Zen
A Bayesian approach to HMM-based speech synthesis. ICASSP 2009: 4029-4032 - [c6]Sayaka Shiota, Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda:
Deterministic annealing based training algorithm for Bayesian speech recognition. INTERSPEECH 2009: 680-683 - [c5]Kei Hashimoto, Yoshihiko Nankaku, Keiichi Tokuda:
A Bayesian approach to Hidden Semi-Markov Model based speech synthesis. INTERSPEECH 2009: 1751-1754 - [c4]Kei Hashimoto, Hirohumi Yamamoto, Hideo Okuma, Eiichiro Sumita, Keiichi Tokuda:
Reordering Model Using Syntactic Information of a Source Tree for Statistical Machine Translation. SSST@HLT-NAACL 2009: 69-77 - 2008
- [c3]Sayaka Shiota, Kei Hashimoto, Heiga Zen, Yoshihiko Nankaku, Akinobu Lee, Keiichi Tokuda:
Acoustic modeling based on model structure annealing for speech recognition. INTERSPEECH 2008: 932-935 - [c2]Kei Hashimoto, Heiga Zen, Yoshihiko Nankaku, Akinobu Lee, Keiichi Tokuda:
Bayesian context clustering using cross valid prior distribution for HMM-based speech recognition. INTERSPEECH 2008: 936-939 - [c1]Tatsuya Ito, Kei Hashimoto, Yoshihiko Nankaku, Akinobu Lee, Keiichi Tokuda:
Speaker recognition based on variational Bayesian method. INTERSPEECH 2008: 1417-1420
Coauthor Index
[c62] [i9] [c61] [c60] [i8] [c59] [i7] [i6] [j10] [j9] [c58] [i5] [i4] [c57] [c56] [c55] [i3] [c54] [c53] [c52] [c51] [c50] [i2] [i1] [j8] [c49] [c48] [c47] [c46] [c45] [c44] [c43] [c42] [c41] [c40] [j7] [c37] [c36] [p1] [j6] [c33] [c32] [c31] [c30] [c29] [c27] [c26] [j5] [c24] [c23] [j4] [c22] [c20] [c19] [c18] [c16] [c15] [c14] [j2] [c11] [c9] [c8] [c7] [c6] [c5] [c3] [c2] [c1]
[c62] [i9] [c61] [c60] [i8] [c59] [i7] [i6] [j10] [j9] [c58] [i5] [i4] [c57] [c56] [c55] [i3] [c54] [c53] [c52] [c51] [c50] [i2] [i1] [j8] [c49] [c48] [c47] [c46] [c45] [c44] [c43] [c42] [c41] [c40] [j7] [c39] [c37] [c36] [p1] [j6] [c35] [c33] [c32] [c31] [c30] [c29] [c28] [c27] [c26] [j5] [c25] [c24] [c23] [j4] [c22] [c21] [c20] [c19] [c18] [j3] [c17] [c16] [c15] [c14] [j2] [c13] [c12] [c11] [c10] [c9] [c8] [j1] [c7] [c6] [c5] [c4] [c3] [c2] [c1]
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