Publications
Blacklisted speaker identification using triplet neural networks. MCE2018 competition.
SUTD_description.pdf (133.08 KB)
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2018. 
Latent space representation for multi-target speaker detection and identification with a sparse dataset using Triplet neural networks. IEEE Automatic Speech Recognition and Understanding Workshop (ASRU 2019).
1910.01463.pdf (934.76 KB)
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2019. 
nnAudio: A PyTorch Audio Processing Tool Using 1D Convolution neural networks. ISMIR - Late Breaking Demo.
nnAudio.pdf (399.08 KB)
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2019. 
The impact of Audio input representations on neural network based music transcription. Proceedings of the International Joint Conference on Neural Networks (IJCNN).
2001.09989.pdf (1.87 MB)
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2020. 
nnAudio: An on-the-fly GPU Audio to Spectrogram Conversion Toolbox Using 1D Convolution Neural Networks. IEEE Access.
nnAudio.pdf (10.2 MB)
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2020. 
Regression-based music emotion prediction using triplet neural networks. Proceedings of the International Joint Conference on Neural Networks (IJCNN).
2001.09988.pdf (777.31 KB)
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2020. 
Unsupervised disentanglement of pitch and timbre for isolated musical instrument sounds. Proceedings of the International Society of Music Information Retrieval (ISMIR).
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2020. The Effect of Spectrogram Reconstructions on Automatic Music Transcription:An Alternative Approach to Improve Transcription Accuracy. Proceedings of the International Conference on Pattern Recognition (ICPR2020).
2010.09969.pdf (3.46 MB)
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2021. 
ReconVAT: A Semi-Supervised Automatic Music Transcription Framework for Low-Resource Real-World Data. ACM Multimedia.
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2021. Revisiting the Onsets and Frames Model with Additive Attention. Proceedings of the International Joint Conference on Neural Networks (IJCNN).
2104.06607.pdf (1.52 MB)
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2021. 
Jointist: Joint Learning for Multi-instrument Transcription and Its Applications.
2206.10805.pdf (427.51 KB)
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2022. 
Understanding Audio Features via Trainable Basis Functions. Arxiv preprint.
2204.11437.pdf (7.36 MB)
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2022. 