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M Huzaifah
M Huzaifah
Agency for Science, Technology and Research
Verified email at i2r.a-star.edu.sg
Title
Cited by
Cited by
Year
Comparison of time-frequency representations for environmental sound classification using convolutional neural networks
M Huzaifah
arXiv preprint arXiv:1706.07156, 2017
2042017
Deep generative models for musical audio synthesis
M Huzaifah, L Wyse
Handbook of artificial intelligence for music: foundations, advanced …, 2021
252021
Applying visual domain style transfer and texture synthesis techniques to audio: Insights and challenges
M Huzaifah, L Wyse
Neural Computing and Applications, 1-15, 2019
25*2019
An analysis of semantically-aligned speech-text embeddings
M Huzaifah, I Kukanov
2022 IEEE Spoken Language Technology Workshop (SLT), 747-754, 2023
5*2023
MTCRNN: A multi-scale rnn for directed audio texture synthesis
M Huzaifah, L Wyse
arXiv preprint arXiv:2011.12596, 2020
52020
Deep learning models for generating audio textures
L Wyse, M Huzaifah
Proceedings of the 2020 Joint Conference on Music Creativity, Stockholm, Sweden, 2020
42020
Conditioning a Recurrent Neural Network to synthesize musical instrument transients
L Wyse, M Huzaifah
Sound and Music Computing Conference, 525-529, 2019
32019
Audio textures in terms of generative models⋆
L Wyse, M Huzaifah
MML 2020, 36, 2020
22020
I2R’s End-to-End Speech Translation System for IWSLT 2023 Offline Shared Task
M Huzaifah, KM Tan, R Duan
Proceedings of the 20th International Conference on Spoken Language …, 2023
12023
Directed Audio Texture Synthesis with Deep Learning
M Huzaifah
National University of Singapore, 2020
2020
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Articles 1–10