Helen Mei-Ling Meng
Artificial Intelligence · 2013–2023
A researcher in the Science corpus: 15 papers; trusts 164 researchers and is trusted by 33 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 253 citations into it; #6,146 of 35,345 by trust here, #7,112 by citations
- Signal Processing — 133 citations into it; #1,435 of 7,572 by trust here, #1,241 by citations
- Speech & Audio — 106 citations into it
- Natural Language Processing — 96 citations into it
- Computer Vision and Pattern Recognition — 58 citations into it
- Generative Models — 42 citations into it
- Model Architectures — 34 citations into it
- Representation & Self-Supervised Learning — 19 citations into it
Whom Helen Mei-Ling Meng trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Alex Graves
- Diederik P. Kingma
- Yoshua Bengio
- Ilya Sutskever
- Alex Krizhevsky
- Yann LeCun
- Kaiming He
- Jimmy Ba
- Tomas Mikolov
Who trusts Helen Mei-Ling Meng overall
- Li Deng
- Zhizheng Wu
- Zhenhua Ling
- Barbara Plank
- Wenya Wang
- Linghui Chen
- Héctor Martínez Alonso
- Dong Yu
Papers from Helen Mei-Ling Meng's perspective
Ordered by how strongly the researchers Helen Mei-Ling Meng trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- Speech Super-Resolution Using Parallel WaveNet (2018) — 21 citations
- Multi-distribution deep belief network for speech synthesis (2013) — 110 citations
- Speech-XLNet: Unsupervised Acoustic Model Pretraining For Self-Attention Networks (2019) — 54 citations
- Phonetic posteriorgrams for many-to-one voice conversion without parallel data training (2016) — 341 citations
- InstructTTS: Modelling Expressive TTS in Discrete Latent Space With Natural Language Style Prompt (2023) — 174 citations
- Fine-grained Opinion Mining with Recurrent Neural Networks and Word Embeddings (2015) — 446 citations
- Speech Representation Disentanglement with Adversarial Mutual Information Learning for One-shot Voice Conversion (2022) — 45 citations
- Towards Identifying Social Bias in Dialog Systems: Framework, Dataset, and Benchmark (2022) — 55 citations
- FullSubNet+: Channel Attention Fullsubnet with Complex Spectrograms for Speech Enhancement (2022) — 152 citations
- Dependency Parsing based Semantic Representation Learning with Graph Neural Network for Enhancing Expressiveness of Text-to-Speech (2021) — 6 citations
- Fcl-Taco2: Towards Fast, Controllable and Lightweight Text-to-Speech Synthesis (2021) — 9 citations
- Towards Multi-Scale Style Control for Expressive Speech Synthesis (2021) — 52 citations
- Any-to-Many Voice Conversion With Location-Relative Sequence-to-Sequence Modeling (2020) — 125 citations
- Code-Switched Speech Synthesis Using Bilingual Phonetic Posteriorgram with Only Monolingual Corpora (2020) — 22 citations
- End-to-end Code-switched TTS with Mix of Monolingual Recordings (2019) — 36 citations