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2020 – today
- 2021
[j12]Toru Nakashika
, Kohei Yatabe:
Gamma Boltzmann Machine for Audio Modeling. IEEE ACM Trans. Audio Speech Lang. Process. 29: 2591-2605 (2021)- [c35]Francisco Mondragon, Jonathan Jimenez, Mariko Nakano, Toru Nakashika, Héctor Pérez-Meana:
Acoustic Scenery Recognition Using CWT and Deep Neural Network. SoMeT 2021: 303-312 - 2020
- [j11]Takuya Kishida, Toru Nakashika:
Speech Chain VC: Linking Linguistic and Acoustic Levels via Latent Distinctive Features for RBM-Based Voice Conversion. IEICE Trans. Inf. Syst. 103-D(11): 2340-2350 (2020) - [c34]Toru Nakashika, Kohei Yatabe:
Gamma Boltzmann Machine for Simultaneously Modeling Linear- and Log-amplitude Spectra. APSIPA 2020: 471-476 - [c33]Toru Nakashika:
Complex-Valued Variational Autoencoder: A Novel Deep Generative Model for Direct Representation of Complex Spectra. INTERSPEECH 2020: 2002-2006 - [c32]Takuya Kishida, Shin Tsukamoto, Toru Nakashika:
Simultaneous Conversion of Speaker Identity and Emotion Based on Multiple-Domain Adaptive RBM. INTERSPEECH 2020: 3431-3435 - [c31]Michel Pezzat, Héctor Manuel Pérez Meana, Toru Nakashika, Mariko Nakano:
Many-to-Many Symbolic Multi-Track Music Genre Transfer. SoMeT 2020: 272-281 - [i3]Toru Nakashika, Kohei Yatabe:
Gamma Boltzmann Machine for Simultaneously Modeling Linear- and Log-amplitude Spectra. CoRR abs/2006.13590 (2020)
2010 – 2019
- 2019
- [j10]Yuki Takashima, Toru Nakashika, Tetsuya Takiguchi, Yasuo Ariki:
Non-parallel dictionary learning for voice conversion using non-negative Tucker decomposition. EURASIP J. Audio Speech Music. Process. 2019: 17 (2019) - [j9]Kentaro Sone, Toru Nakashika:
Pre-Training of DNN-Based Speech Synthesis Based on Bidirectional Conversion between Text and Speech. IEICE Trans. Inf. Syst. 102-D(8): 1546-1553 (2019) - [j8]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) - [c30]Shinji Takaki, Toru Nakashika, Xin Wang, Junichi Yamagishi:
STFT Spectral Loss for Training a Neural Speech Waveform Model. ICASSP 2019: 7065-7069 - 2018
- [j7]Toru Nakashika:
Deep Relational Model: A Joint Probabilistic Model with a Hierarchical Structure for Bidirectional Estimation of Image and Labels. IEICE Trans. Inf. Syst. 101-D(2): 428-436 (2018) - [c29]Yuki Takashima, Hajime Yano, Toru Nakashika, Tetsuya Takiguchi, Yasuo Ariki:
Parallel-Data-Free Dictionary Learning for Voice Conversion Using Non-Negative Tucker Decomposition. ICASSP 2018: 5294-5298 - [c28]Kentaro Sone, Toru Nakashika:
DNN-based Speech Synthesis for Small Data Sets Considering Bidirectional Speech-Text Conversion. INTERSPEECH 2018: 2519-2523 - [c27]Toru Nakashika:
LSTBM: A Novel Sequence Representation of Speech Spectra Using Restricted Boltzmann Machine with Long Short-Term Memory. INTERSPEECH 2018: 2529-2533 - [c26]Kentaro Sone, Shinji Takaki, Toru Nakashika:
Bidirectional Voice Conversion Based on Joint Training Using Gaussian-Gaussian Deep Relational Model. Odyssey 2018: 261-266 - [i2]Toru Nakashika, Shinji Takaki, Junichi Yamagishi:
Complex-Valued Restricted Boltzmann Machine for Direct Speech Parameterization from Complex Spectra. CoRR abs/1803.09946 (2018) - [i1]Shinji Takaki, Toru Nakashika, Xin Wang, Junichi Yamagishi:
STFT spectral loss for training a neural speech waveform model. CoRR abs/1810.11945 (2018) - 2017
- [j6]Toru Nakashika, Yasuhiro Minami:
Speaker-adaptive-trainable Boltzmann machine and its application to non-parallel voice conversion. EURASIP J. Audio Speech Music. Process. 2017: 16 (2017) - [c25]Toru Nakashika:
CAB: An Energy-Based Speaker Clustering Model for Rapid Adaptation in Non-Parallel Voice Conversion. INTERSPEECH 2017: 3369-3373 - [c24]Toru Nakashika, Shinji Takaki, Junichi Yamagishi:
Complex-Valued Restricted Boltzmann Machine for Direct Learning of Frequency Spectra. INTERSPEECH 2017: 4021-4025 - 2016
- [j5]Toru Nakashika, Tetsuya Takiguchi, Yasuhiro Minami:
Non-Parallel Training in Voice Conversion Using an Adaptive Restricted Boltzmann Machine. IEEE ACM Trans. Audio Speech Lang. Process. 24(11): 2032-2045 (2016) - [c23]Yuichiro Kataoka, Toru Nakashika, Ryo Aihara, Tetsuya Takiguchi, Yasuo Ariki:
Selection of an optimum random matrix using a genetic algorithm for acoustic feature extraction. ICIS 2016: 1-6 - [c22]Toru Nakashika, Yasuhiro Minami:
3WRBM-based speech factor modeling for arbitrary-source and non-parallel voice conversion. EUSIPCO 2016: 607-611 - [c21]Toru Nakashika, Tetsuya Takiguchi, Yasuo Ariki:
Modeling deep bidirectional relationships for image classification and generation. ICASSP 2016: 1327-1331 - [c20]Toru Nakashika, Yasuhiro Minami:
Speaker adaptive model based on Boltzmann machine for non-parallel training in voice conversion. ICASSP 2016: 5530-5534 - [c19]Toru Nakashika, Yasuhiro Minami:
Generative Acoustic-Phonemic-Speaker Model Based on Three-Way Restricted Boltzmann Machine. INTERSPEECH 2016: 1487-1491 - 2015
- [j4]Toru Nakashika, Tetsuya Takiguchi, Yasuo Ariki:
Voice conversion using speaker-dependent conditional restricted Boltzmann machine. EURASIP J. Audio Speech Music. Process. 2015: 8 (2015) - [j3]Ryo Aihara, Takao Fujii, Toru Nakashika, Tetsuya Takiguchi, Yasuo Ariki:
Small-parallel exemplar-based voice conversion in noisy environments using affine non-negative matrix factorization. EURASIP J. Audio Speech Music. Process. 2015: 32 (2015) - [j2]Toru Nakashika, Tetsuya Takiguchi, Yasuo Ariki:
Voice Conversion Using RNN Pre-Trained by Recurrent Temporal Restricted Boltzmann Machines. IEEE ACM Trans. Audio Speech Lang. Process. 23(3): 580-587 (2015) - [c18]Ryo Aihara, Takao Fujii, Toru Nakashika, Tetsuya Takiguchi, Yasuo Ariki:
Noise-robust voice conversion using a small parallel data based on non-negative matrix factorization. EUSIPCO 2015: 315-319 - [c17]Yuki Takashima, Toru Nakashika, Tetsuya Takiguchi, Yasuo Ariki:
Feature extraction using pre-trained convolutive bottleneck nets for dysarthric speech recognition. EUSIPCO 2015: 1411-1415 - [c16]Toru Nakashika, Tetsuya Takiguchi, Yasuo Ariki:
Sparse nonlinear representation for voice conversion. ICME 2015: 1-6 - [c15]Jinhui Chen, Toru Nakashika, Tetsuya Takiguchi, Yasuo Ariki:
Content-based Image Retrieval Using Rotation-invariant Histograms of Oriented Gradients. ICMR 2015: 443-446 - 2014
- [j1]Toru Nakashika, Tetsuya Takiguchi, Yasuo Ariki:
Voice Conversion Based on Speaker-Dependent Restricted Boltzmann Machines. IEICE Trans. Inf. Syst. 97-D(6): 1403-1410 (2014) - [c14]Toru Nakashika, Tetsuya Takiguchi, Yasuo Ariki:
Voice conversion in time-invariant speaker-independent space. ICASSP 2014: 7889-7893 - [c13]Ryo Aihara, Toru Nakashika, Tetsuya Takiguchi, Yasuo Ariki:
Voice conversion based on Non-negative matrix factorization using phoneme-categorized dictionary. ICASSP 2014: 7894-7898 - [c12]Toru Nakashika, Takafumi Hori, Tetsuya Takiguchi, Yasuo Ariki:
3D-Object Recognition Based on LLC Using Depth Spatial Pyramid. ICPR 2014: 4224-4228 - [c11]Toru Nakashika, Tetsuya Takiguchi, Yasuo Ariki:
High-order sequence modeling using speaker-dependent recurrent temporal restricted boltzmann machines for voice conversion. INTERSPEECH 2014: 2278-2282 - [c10]E. Byambakhishig, Katsuyuki Tanaka, Ryo Aihara, Toru Nakashika, Tetsuya Takiguchi, Yasuo Ariki:
Error correction of automatic speech recognition based on normalized web distance. INTERSPEECH 2014: 2852-2856 - 2013
- [c9]Julien N. P. Martel, Toru Nakashika, Christophe Garcia, Khalid Idrissi:
A Combination of Hand-Crafted and Hierarchical High-Level Learnt Feature Extraction for Music Genre Classification. ICANN 2013: 397-404 - [c8]Toru Nakashika, Takeshi Okumura, Tetsuya Takiguchi, Yasuo Ariki:
Sparse representation for outliers suppression in semi-supervised image annotation. ICASSP 2013: 2080-2083 - [c7]Toru Nakashika, Ryoichi Takashima, Tetsuya Takiguchi, Yasuo Ariki:
Voice conversion in high-order eigen space using deep belief nets. INTERSPEECH 2013: 369-372 - [c6]Toru Nakashika, Tetsuya Takiguchi, Yasuo Ariki:
High-Frequency Restoration Using Deep Belief Nets for Super-resolution. SITIS 2013: 38-42 - 2012
- [c5]Toru Nakashika, Christophe Garcia, Tetsuya Takiguchi:
Local-feature-map Integration Using Convolutional Neural Networks for Music Genre Classification. INTERSPEECH 2012: 1752-1755 - 2011
- [c4]Toru Nakashika, Akira Suga, Tetsuya Takiguchi, Yasuo Ariki:
Generic object recognition using automatic region extraction and dimensional feature integration utilizing multiple kernel learning. ICASSP 2011: 1229-1232 - [c3]Toru Nakashika, Tetsuya Takiguchi, Yasuo Ariki:
Probabilistic Spectrum Envelope: Categorized Audio-Features Representation for NMF-Based Sound Decomposition. INTERSPEECH 2011: 1765-1768 - [c2]Toru Nakashika, Tetsuya Takiguchi, Yasuo Ariki:
Constrained Spectrum Generation Using A Probabilistic Spectrum Envelope for Mixed Music Analysis. ISMIR 2011: 181-184 - 2010
- [c1]Toru Nakashika, Ryuki Tachibana, Masafumi Nishimura, Tetsuya Takiguchi, Yasuo Ariki:
Speech synthesis by modeling harmonics structure with multiple function. INTERSPEECH 2010: 945-948
Coauthor Index
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