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ORCIDShinji Takaki
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2020 – today
- 2023
[c37]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- 2022
- [i14]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) - 2021
- [j11]Yukiya Hono
, Shinji Takaki, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
PeriodNet: A Non-Autoregressive Raw Waveform Generative Model With a Structure Separating Periodic and Aperiodic Components. IEEE Access 9: 137599-137612 (2021) - [c36]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 - [i13]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) - 2020
- [j10]Shuhei Kato, Yusuke Yasuda, Xin Wang, Erica Cooper, Shinji Takaki, Junichi Yamagishi:
Modeling of Rakugo Speech and Its Limitations: Toward Speech Synthesis That Entertains Audiences. IEEE Access 8: 138149-138161 (2020) - [j9]Xin Wang, Shinji Takaki, Junichi Yamagishi, Simon King, Keiichi Tokuda:
A Vector Quantized Variational Autoencoder (VQ-VAE) Autoregressive Neural F0 Model for Statistical Parametric Speech Synthesis. IEEE ACM Trans. Audio Speech Lang. Process. 28: 157-170 (2020) - [j8]Xin Wang, Shinji Takaki, Junichi Yamagishi:
Neural Source-Filter Waveform Models for Statistical Parametric Speech Synthesis. IEEE ACM Trans. Audio Speech Lang. Process. 28: 402-415 (2020) - [c35]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 - [c34]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
2010 – 2019
- 2019
- [j7]Toru Nakashika, Shinji Takaki, Junichi Yamagishi:
Complex-Valued Restricted Boltzmann Machine for Speaker-Dependent Speech Parameterization From Complex Spectra. IEEE ACM Trans. Audio Speech Lang. Process. 27(2): 244-254 (2019) - [c33]Xin Wang, Shinji Takaki, Junichi Yamagishi:
Neural Source-filter-based Waveform Model for Statistical Parametric Speech Synthesis. ICASSP 2019: 5916-5920 - [c32]Yusuke Yasuda, Xin Wang, Shinji Takaki, Junichi Yamagishi:
Investigation of Enhanced Tacotron Text-to-speech Synthesis Systems with Self-attention for Pitch Accent Language. ICASSP 2019: 6905-6909 - [c31]Shinji Takaki, Toru Nakashika, Xin Wang, Junichi Yamagishi:
STFT Spectral Loss for Training a Neural Speech Waveform Model. ICASSP 2019: 7065-7069 - [c30]Yi Zhao, Atsushi Ando, Shinji Takaki, Junichi Yamagishi, Satoshi Kobashikawa:
Does the Lombard Effect Improve Emotional Communication in Noise? - Analysis of Emotional Speech Acted in Noise. INTERSPEECH 2019: 3292-3296 - [c29]Shuhei Kato, Yusuke Yasuda, Xin Wang, Erica Cooper, Shinji Takaki, Junichi Yamagishi:
Rakugo speech synthesis using segment-to-segment neural transduction and style tokens - toward speech synthesis for entertaining audiences. SSW 2019: 111-116 - [i12]Yi Zhao, Atsushi Ando, Shinji Takaki, Junichi Yamagishi, Satoshi Kobashikawa:
Does the Lombard Effect Improve Emotional Communication in Noise? - Analysis of Emotional Speech Acted in Noise -. CoRR abs/1903.12316 (2019) - [i11]Shinji Takaki, Hirokazu Kameoka, Junichi Yamagishi:
Training a Neural Speech Waveform Model using Spectral Losses of Short-Time Fourier Transform and Continuous Wavelet Transform. CoRR abs/1903.12392 (2019) - [i10]Xin Wang, Shinji Takaki, Junichi Yamagishi:
Neural source-filter waveform models for statistical parametric speech synthesis. CoRR abs/1904.12088 (2019) - [i9]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) - [i8]Seyyed Saeed Sarfjoo, Xin Wang, Gustav Eje Henter, Jaime Lorenzo-Trueba, Shinji Takaki, Junichi Yamagishi:
Transformation of low-quality device-recorded speech to high-quality speech using improved SEGAN model. CoRR abs/1911.03952 (2019) - 2018
- [j6]Yi Zhao, Shinji Takaki, Hieu-Thi Luong, Junichi Yamagishi, Daisuke Saito, Nobuaki Minematsu:
Wasserstein GAN and Waveform Loss-Based Acoustic Model Training for Multi-Speaker Text-to-Speech Synthesis Systems Using a WaveNet Vocoder. IEEE Access 6: 60478-60488 (2018) - [j5]Xin Wang, Shinji Takaki, Junichi Yamagishi:
Investigating very deep highway networks for parametric speech synthesis. Speech Commun. 96: 1-9 (2018) - [j4]Jaime Lorenzo-Trueba, Gustav Eje Henter, Shinji Takaki, Junichi Yamagishi, Yosuke Morino, Yuta Ochiai:
Investigating different representations for modeling and controlling multiple emotions in DNN-based speech synthesis. Speech Commun. 99: 135-143 (2018) - [j3]Xin Wang, Shinji Takaki, Junichi Yamagishi:
Autoregressive Neural F0 Model for Statistical Parametric Speech Synthesis. IEEE ACM Trans. Audio Speech Lang. Process. 26(8): 1406-1419 (2018) - [c28]Shinji Takaki, Yoshikazu Nishimura, Junichi Yamagishi:
Unsupervised Speaker Adaptation for DNN-based Speech Synthesis using Input Codes. APSIPA 2018: 649-658 - [c27]Xin Wang, Jaime Lorenzo-Trueba, Shinji Takaki, Lauri Juvela, Junichi Yamagishi:
A Comparison of Recent Waveform Generation and Acoustic Modeling Methods for Neural-Network-Based Speech Synthesis. ICASSP 2018: 4804-4808 - [c26]Kentaro Sone, Shinji Takaki, Toru Nakashika:
Bidirectional Voice Conversion Based on Joint Training Using Gaussian-Gaussian Deep Relational Model. Odyssey 2018: 261-266 - [i7]Toru Nakashika, Shinji Takaki, Junichi Yamagishi:
Complex-Valued Restricted Boltzmann Machine for Direct Speech Parameterization from Complex Spectra. CoRR abs/1803.09946 (2018) - [i6]Xin Wang, Jaime Lorenzo-Trueba, Shinji Takaki, Lauri Juvela, Junichi Yamagishi:
A comparison of recent waveform generation and acoustic modeling methods for neural-network-based speech synthesis. CoRR abs/1804.02549 (2018) - [i5]Yi Zhao, Shinji Takaki, Hieu-Thi Luong, Junichi Yamagishi, Daisuke Saito, Nobuaki Minematsu:
Wasserstein GAN and Waveform Loss-based Acoustic Model Training for Multi-speaker Text-to-Speech Synthesis Systems Using a WaveNet Vocoder. CoRR abs/1807.11679 (2018) - [i4]Shinji Takaki, Toru Nakashika, Xin Wang, Junichi Yamagishi:
STFT spectral loss for training a neural speech waveform model. CoRR abs/1810.11945 (2018) - [i3]Xin Wang, Shinji Takaki, Junichi Yamagishi:
Neural source-filter-based waveform model for statistical parametric speech synthesis. CoRR abs/1810.11946 (2018) - [i2]Yusuke Yasuda, Xin Wang, Shinji Takaki, Junichi Yamagishi:
Investigation of enhanced Tacotron text-to-speech synthesis systems with self-attention for pitch accent language. CoRR abs/1810.11960 (2018) - 2017
- [c25]Xin Wang, Shinji Takaki, Junichi Yamagishi:
An autoregressive recurrent mixture density network for parametric speech synthesis. ICASSP 2017: 4895-4899 - [c24]Hieu-Thi Luong, Shinji Takaki, Gustav Eje Henter, Junichi Yamagishi:
Adapting and controlling DNN-based speech synthesis using input codes. ICASSP 2017: 4905-4909 - [c23]Xin Wang, Shinji Takaki, Junichi Yamagishi:
An RNN-Based Quantized F0 Model with Multi-Tier Feedback Links for Text-to-Speech Synthesis. INTERSPEECH 2017: 1059-1063 - [c22]Shinji Takaki, Hirokazu Kameoka, Junichi Yamagishi:
Direct Modeling of Frequency Spectra and Waveform Generation Based on Phase Recovery for DNN-Based Speech Synthesis. INTERSPEECH 2017: 1128-1132 - [c21]Takuhiro Kaneko, Shinji Takaki, Hirokazu Kameoka, Junichi Yamagishi:
Generative Adversarial Network-Based Postfilter for STFT Spectrograms. INTERSPEECH 2017: 3389-3393 - [c20]Toru Nakashika, Shinji Takaki, Junichi Yamagishi:
Complex-Valued Restricted Boltzmann Machine for Direct Learning of Frequency Spectra. INTERSPEECH 2017: 4021-4025 - 2016
- [j2]Xin Wang, Shinji Takaki, Junichi Yamagishi:
Investigation of Using Continuous Representation of Various Linguistic Units in Neural Network Based Text-to-Speech Synthesis. IEICE Trans. Inf. Syst. 99-D(10): 2471-2480 (2016) - [c19]Lauri Juvela, Xin Wang, Shinji Takaki, Sangjin Kim, Manu Airaksinen, Junichi Yamagishi:
The NII speech synthesis entry for Blizzard Challenge 2016. Blizzard Challenge 2016 - [c18]Shinji Takaki, Junichi Yamagishi:
A deep auto-encoder based low-dimensional feature extraction from FFT spectral envelopes for statistical parametric speech synthesis. ICASSP 2016: 5535-5539 - [c17]Cassia Valentini-Botinhao, Xin Wang, Shinji Takaki, Junichi Yamagishi:
Speech Enhancement for a Noise-Robust Text-to-Speech Synthesis System Using Deep Recurrent Neural Networks. INTERSPEECH 2016: 352-356 - [c16]Lauri Juvela, Xin Wang, Shinji Takaki, Manu Airaksinen, Junichi Yamagishi, Paavo Alku:
Using Text and Acoustic Features in Predicting Glottal Excitation Waveforms for Parametric Speech Synthesis with Recurrent Neural Networks. INTERSPEECH 2016: 2283-2287 - [c15]Xin Wang, Shinji Takaki, Junichi Yamagishi:
Enhance the Word Vector with Prosodic Information for the Recurrent Neural Network Based TTS System. INTERSPEECH 2016: 2856-2860 - [c14]Xin Wang, Shinji Takaki, Junichi Yamagishi:
A Comparative Study of the Performance of HMM, DNN, and RNN based Speech Synthesis Systems Trained on Very Large Speaker-Dependent Corpora. SSW 2016: 118-121 - [c13]Cassia Valentini-Botinhao, Xin Wang, Shinji Takaki, Junichi Yamagishi:
Investigating RNN-based speech enhancement methods for noise-robust Text-to-Speech. SSW 2016: 146-152 - [c12]Shinji Takaki, Sangjin Kim, Junichi Yamagishi:
Speaker Adaptation of Various Components in Deep Neural Network based Speech Synthesis. SSW 2016: 153-159 - [c11]Xin Wang, Shinji Takaki, Junichi Yamagishi:
Investigating Very Deep Highway Networks for Parametric Speech Synthesis. SSW 2016: 166-171 - [p1]Shinji Takaki, Junichi Yamagishi:
Constructing a Deep Neural Network Based Spectral Model for Statistical Speech Synthesis. Recent Advances in Nonlinear Speech Processing 2016: 117-125 - 2015
- [c10]Shinji Takaki, Sangjin Kim, Junichi Yamagishi, JongJin Kim:
Multiple feed-forward deep neural networks for statistical parametric speech synthesis. INTERSPEECH 2015: 2242-2246 - [c9]Eita Nakamura, Shinji Takaki:
Characteristics of Polyphonic Music Style and Markov Model of Pitch-Class Intervals. MCM 2015: 109-114 - [i1]Zhenzhou Wu, Shinji Takaki, Junichi Yamagishi:
Deep Denoising Auto-encoder for Statistical Speech Synthesis. CoRR abs/1506.05268 (2015) - 2014
- [j1]Shinji Takaki, Yoshihiko Nankaku, Keiichi Tokuda:
Contextual Additive Structure for HMM-Based Speech Synthesis. IEEE J. Sel. Top. Signal Process. 8(2): 229-238 (2014) - [c8]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 - 2013
- [c7]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 - [c6]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 - [c5]Shinji Takaki, Yoshihiko Nankaku, Keiichi Tokuda:
Contextual partial additive structure for HMM-based speech synthesis. ICASSP 2013: 7878-7882 - 2012
- [c4]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 - 2011
- [c3]Kei Hashimoto, Shinji Takaki, Keiichiro Oura, Keiichi Tokuda:
Overview of NIT HMM-based speech synthesis system for Blizzard Challenge 2011. Blizzard Challenge 2011 - [c2]Shinji Takaki, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda:
An optimization algorithm of independent mean and variance parameter tying structures for HMM-based speech synthesis. ICASSP 2011: 4700-4703 - 2010
- [c1]Shinji Takaki, Yoshihiko Nankaku, Keiichi Tokuda:
Spectral modeling with contextual additive structure for HMM-based speech synthesis. SSW 2010: 100-105
Coauthor Index
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last updated on 2024-09-28 01:29 CEST by the dblp team
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