| Description and discussion on DCASE2020 challenge task2: Unsupervised anomalous sound detection for machine condition monitoring Y Koizumi, Y Kawaguchi, K Imoto, T Nakamura, Y Nikaido, R Tanabe, ... arXiv preprint arXiv:2006.05822, 2020 | 241 | 2020 |
| ToyADMOS: A dataset of miniature-machine operating sounds for anomalous sound detection Y Koizumi, S Saito, H Uematsu, N Harada, K Imoto 2019 IEEE Workshop on Applications of Signal Processing to Audio and …, 2019 | 235 | 2019 |
| Unsupervised detection of anomalous sound based on deep learning and the neyman–pearson lemma Y Koizumi, S Saito, H Uematsu, Y Kawachi, N Harada IEEE/ACM Transactions on Audio, Speech, and Language Processing 27 (1), 212-224, 2018 | 189 | 2018 |
| Speech enhancement using self-adaptation and multi-head self-attention Y Koizumi, K Yatabe, M Delcroix, Y Masuyama, D Takeuchi ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 148 | 2020 |
| Complementary set variational autoencoder for supervised anomaly detection Y Kawachi, Y Koizumi, N Harada 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 131 | 2018 |
| Description and discussion on DCASE 2022 challenge task 2: Unsupervised anomalous sound detection for machine condition monitoring applying domain generalization techniques K Dohi, K Imoto, N Harada, D Niizumi, Y Koizumi, T Nishida, H Purohit, ... arXiv preprint arXiv:2206.05876, 2022 | 112 | 2022 |
| Description and discussion on DCASE 2021 challenge task 2: Unsupervised anomalous sound detection for machine condition monitoring under domain shifted conditions Y Kawaguchi, K Imoto, Y Koizumi, N Harada, D Niizumi, K Dohi, ... arXiv preprint arXiv:2106.04492, 2021 | 91 | 2021 |
| Optimizing acoustic feature extractor for anomalous sound detection based on Neyman-Pearson lemma Y Koizumi, S Saito, H Uematsu, N Harada 2017 25th European Signal Processing Conference (EUSIPCO), 698-702, 2017 | 90 | 2017 |
| DNN-based source enhancement to increase objective sound quality assessment score Y Koizumi, K Niwa, Y Hioka, K Kobayashi, Y Haneda IEEE/ACM Transactions on Audio, Speech, and Language Processing 26 (10 …, 2018 | 75 | 2018 |
| A transformer-based audio captioning model with keyword estimation Y Koizumi, R Masumura, K Nishida, M Yasuda, S Saito arXiv preprint arXiv:2007.00222, 2020 | 74 | 2020 |
| Deep griffin–lim iteration Y Masuyama, K Yatabe, Y Koizumi, Y Oikawa, N Harada ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 72 | 2019 |
| DNN-based Source Enhancement Self-optimized by Reinforcement Learning using Sound Quality Measurements Yuma Koizumi, Kenta Niwa, Yusuke Hioka, Kazunori Kobayashi, Yoichi Haneda Acoustics, Speech and Signal Processing (ICASSP), 2017 IEEE International …, 2017 | 62* | 2017 |
| Listen to what you want: Neural network-based universal sound selector T Ochiai, M Delcroix, Y Koizumi, H Ito, K Kinoshita, S Araki arXiv preprint arXiv:2006.05712, 2020 | 59 | 2020 |
| Real-time speech enhancement using equilibriated RNN D Takeuchi, K Yatabe, Y Koizumi, Y Oikawa, N Harada ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 59 | 2020 |
| Sound event detection by multitask learning of sound events and scenes with soft scene labels K Imoto, N Tonami, Y Koizumi, M Yasuda, R Yamanishi, Y Yamashita ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 57 | 2020 |
| Description and discussion on DCASE 2023 challenge task 2: First-shot unsupervised anomalous sound detection for machine condition monitoring K Dohi, K Imoto, N Harada, D Niizumi, Y Koizumi, T Nishida, H Purohit, ... arXiv preprint arXiv:2305.07828, 2023 | 55 | 2023 |
| DF-Conformer: Integrated architecture of Conv-TasNet and Conformer using linear complexity self-attention for speech enhancement Y Koizumi, S Karita, S Wisdom, H Erdogan, JR Hershey, L Jones, ... 2021 IEEE Workshop on Applications of Signal Processing to Audio and …, 2021 | 50 | 2021 |
| SNIPER: Few-shot learning for anomaly detection to minimize false-negative rate with ensured true-positive rate Y Koizumi, S Murata, N Harada, S Saito, H Uematsu ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 48 | 2019 |
| Noisy-target training: A training strategy for DNN-based speech enhancement without clean speech T Fujimura, Y Koizumi, K Yatabe, R Miyazaki 2021 29th european signal processing conference (EUSIPCO), 436-440, 2021 | 47 | 2021 |
| Audio captioning using pre-trained large-scale language model guided by audio-based similar caption retrieval Y Koizumi, Y Ohishi, D Niizumi, D Takeuchi, M Yasuda arXiv preprint arXiv:2012.07331, 2020 | 46 | 2020 |
Noboru HaradaNTT Communication Science Laboratories確認したメール アドレス: ieee.org
