Robust sequence-to-sequence acoustic modeling with stepwise monotonic attention for neural TTS M He, Y Deng, L He Interspeech 2019, 2019 | 101 | 2019 |
Neural subgraph isomorphism counting X Liu, H Pan, M He, Y Song, X Jiang, L Shang Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 88 | 2020 |
Time-evolving Text Classification with Deep Neural Networks Y He, J Li, Y Song, M He, H Peng IJCAI 18, 2241-2247, 2018 | 62 | 2018 |
Can ChatGPT Detect Intent? Evaluating Large Language Models for Spoken Language Understanding M He, PN Garner Interspeech 2023, 2023 | 43 | 2023 |
Acquiring and modeling abstract commonsense knowledge via conceptualization M He, T Fang, W Wang, Y Song Artificial Intelligence 333, 104149, 2024 | 32 | 2024 |
Multilingual Byte2Speech Models for Scalable Low-resource Speech Synthesis M He, J Yang, L He, FK Soong arXiv preprint arXiv:2103.03541, 2021 | 32* | 2021 |
On the role of conceptualization in commonsense knowledge graph construction M He, Y Song, K Xu, D Yu arXiv preprint arXiv:2003.03239, 2020 | 13 | 2020 |
The Interpreter Understands Your Meaning: End-to-end Spoken Language Understanding Aided by Speech Translation M He, PN Garner Findings of EMNLP 2023, 2023 | 3 | 2023 |
The Idiap Speech Synthesis System for the Blizzard Challenge 2023 H Chen, M He, LC de Gibson, PN Garner Proc. 18th Blizzard Challenge Workshop, 93-97, 2023 | 1 | 2023 |
Neural lexicon reader: Reduce pronunciation errors in end-to-end tts by leveraging external textual knowledge M He, J Yang, L He, FK Soong Interspeech 2022, 2021 | 1 | 2021 |
Joint Fine-tuning and Conversion of Pretrained Speech and Language Models towards Linear Complexity M He, PN Garner ICLR 2025, 2024 | | 2024 |