Max W. Y. Lam

According to our database1, Max W. Y. Lam authored at least 26 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
SongCreator: Lyrics-based Universal Song Generation.
CoRR, 2024

Foundation Models for Music: A Survey.
CoRR, 2024

2023
Efficient Neural Music Generation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Diverse and Expressive Speech Prosody Prediction with Denoising Diffusion Probabilistic Model.
Proceedings of the 24th Annual Conference of the International Speech Communication Association, 2023

2022
FastDiff: A Fast Conditional Diffusion Model for High-Quality Speech Synthesis.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

BDDM: Bilateral Denoising Diffusion Models for Fast and High-Quality Speech Synthesis.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Bilateral Denoising Diffusion Models.
CoRR, 2021

Effective Low-Cost Time-Domain Audio Separation Using Globally Attentive Locally Recurrent Networks.
Proceedings of the IEEE Spoken Language Technology Workshop, 2021

Raw Waveform Encoder with Multi-Scale Globally Attentive Locally Recurrent Networks for End-to-End Speech Recognition.
Proceedings of the 22nd Annual Conference of the International Speech Communication Association, Interspeech 2021, Brno, Czechia, August 30, 2021

Contrastive Separative Coding for Self-Supervised Representation Learning.
Proceedings of the IEEE International Conference on Acoustics, 2021

Sandglasset: A Light Multi-Granularity Self-Attentive Network for Time-Domain Speech Separation.
Proceedings of the IEEE International Conference on Acoustics, 2021

Tune-In: Training Under Negative Environments with Interference for Attention Networks Simulating Cocktail Party Effect.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Mixup-breakdown: A Consistency Training Method for Improving Generalization of Speech Separation Models.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
Comparative Study of Parametric and Representation Uncertainty Modeling for Recurrent Neural Network Language Models.
Proceedings of the 20th Annual Conference of the International Speech Communication Association, 2019

Extract, Adapt and Recognize: An End-to-End Neural Network for Corrupted Monaural Speech Recognition.
Proceedings of the 20th Annual Conference of the International Speech Communication Association, 2019

LF-MMI Training of Bayesian and Gaussian Process Time Delay Neural Networks for Speech Recognition.
Proceedings of the 20th Annual Conference of the International Speech Communication Association, 2019

Recurrent Neural Network Language Model Training Using Natural Gradient.
Proceedings of the IEEE International Conference on Acoustics, 2019

Gaussian Process Lstm Recurrent Neural Network Language Models for Speech Recognition.
Proceedings of the IEEE International Conference on Acoustics, 2019

Bayesian and Gaussian Process Neural Networks for Large Vocabulary Continuous Speech Recognition.
Proceedings of the IEEE International Conference on Acoustics, 2019

2018
One-Match-Ahead Forecasting in Two-Team Sports with Stacked Bayesian Regressions.
J. Artif. Intell. Soft Comput. Res., 2018

Development of the CUHK Dysarthric Speech Recognition System for the UA Speech Corpus.
Proceedings of the 19th Annual Conference of the International Speech Communication Association, 2018

Gaussian Process Neural Networks for Speech Recognition.
Proceedings of the 19th Annual Conference of the International Speech Communication Association, 2018

Drawing-Based Automatic Dementia Screening Using Gaussian Process Markov Chains.
Proceedings of the 51st Hawaii International Conference on System Sciences, 2018

Machine Learning on Drawing Behavior for Dementia Screening.
Proceedings of the 2018 International Conference on Digital Health, 2018

2017
TLGProb: Two-Layer Gaussian Process Regression Model for Winning Probability Calculation in Two-Team Sports.
Proceedings of the Artificial Intelligence and Soft Computing, 2017

Classification of Visit-to-Visit Blood Pressure Variability: A Machine Learning Approach for Data Clustering on Systolic Blood Pressure Intervention Trial (SPRINT).
Proceedings of the 2017 International Conference on Digital Health, 2017


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