| Speech emotion recognition using 3d convolutions and attention-based sliding recurrent networks with auditory front-ends Z Peng, X Li, Z Zhu, M Unoki, J Dang, M Akagi IEEE Access 8, 16560-16572, 2020 | 69 | 2020 |
| Improving multilingual speech emotion recognition by combining acoustic features in a three-layer model X Li, M Akagi Speech Communication 110, 1--12, 2019 | 41 | 2019 |
| Multilingual Speech Emotion Recognition System Based on a Three-Layer Model. X Li, M Akagi Interspeech, 3608-3612, 2016 | 21 | 2016 |
| A three-layer emotion perception model for valence and arousal-based detection from multilingual speech X Li, M Akagi International Speech Communication Association, 2018 | 15 | 2018 |
| Toward improving estimation accuracy of emotion dimensions in bilingual scenario based on three-layered model X Li, M Akagi 2015 International Conference Oriental COCOSDA held jointly with 2015 …, 2015 | 5 | 2015 |
| Machine learning-based prediction model for distant metastasis of breast cancer H Duan, Y Zhang, H Qiu, X Fu, C Liu, X Zang, A Xu, Z Wu, X Li, Q Zhang, ... Computers in Biology and Medicine 169, 107943, 2024 | 3 | 2024 |
| Emotion Awareness in Multi-utterance Turn for Improving Emotion Prediction in Multi-Speaker Conversation X Shi, X Li, T Toda INTERSPEECH2023, 765-769, 2023 | 3 | 2023 |
| Music Theory-inspired Acoustic Representation for Speech Emotion Recognition X Li, X Shi, D Hu, Y Li, Q Zhang, Z Wang, M Unoki, M Akagi IEEE/ACM Transactions on Audio, Speech, and Language Processing 31, 2534 - 2547, 2023 | 3 | 2023 |
| Automatic speech emotion recognition in chinese using a three-layered model in dimensional approach X Li, M Akagi 2016 RISP International Workshop on Nonlinear Circuits, Communications and …, 2016 | 3 | 2016 |
| Semi-supervised multimodal emotion recognition with consensus decision-making and label correction J Tian, D Hu, X Shi, J He, X Li, Y Gao, T Toda, X Xu, X Hu Proceedings of the 1st International Workshop on Multimodal and Responsible …, 2023 | 2 | 2023 |
| On the effectiveness of asr representations in real-world noisy speech emotion recognition X Shi, J He, X Li, T Toda arXiv preprint arXiv:2311.07093, 2023 | 1 | 2023 |
| Hierarchical Prosody Analysis Improves Categorical and Dimensional Emotion Recognition X Li, T Guo, X Hu, X Xu, J Dang, M Akagi 2021 Asia-Pacific Signal and Information Processing Association Annual …, 2021 | 1 | 2021 |
| MF-AED-AEC: Speech Emotion Recognition by Leveraging Multimodal Fusion, ASR Error Detection, and ASR Error Correction J He, X Shi, X Li, T Toda ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | | 2024 |
| The Contribution of Acoustic Features Analysis to Model Emotion Perceptual Process for Language Diversity X Li, M Akagi Proc. Interspeech 2019, 3262-3266, 2019 | | 2019 |
| Maximal Information Coefficient and Predominant Correlation-Based Feature Selection Toward A Three-Layer Model for Speech Emotion Recognition X Li, M Akagi APSIPA Annual Summit and Conference 2018, 1428-1434, 2018 | | 2018 |
| Improving Estimation Accuracy of Dimension Values for Speech Emotion in Bilingual Cases Using a Three-layered Model LI Xingfeng, M AKAGI 聴覚研究会資料= Proceedings of the auditory research meeting 45 (7), 577-581, 2015 | | 2015 |
Masato AkagiProfessor of Japan Advanced Institute of Science and TechnologyVerified email at jaist.ac.jp
