Unsupervised learning of deep features for music segmentation MC McCallum ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 46 | 2019 |
Stochastic-deterministic MMSE STFT speech enhancement with general a priori information M McCallum, B Guillemin IEEE transactions on audio, speech, and language processing 21 (7), 1445-1457, 2013 | 42 | 2013 |
The Harmonix Set: Beats, Downbeats, and Functional Segment Annotations of Western Popular Music. O Nieto, MC McCallum, MEP Davies, A Robertson, AM Stark, E Egozy ISMIR, 565-572, 2019 | 40 | 2019 |
Supervised and unsupervised learning of audio representations for music understanding MC McCallum, F Korzeniowski, S Oramas, F Gouyon, AF Ehmann arXiv preprint arXiv:2210.03799, 2022 | 35 | 2022 |
Methods and apparatus to segment audio and determine audio segment similarities M McCallum US Patent 11,024,288, 2021 | 17 | 2021 |
Mood classification using listening data F Korzeniowski, O Nieto, M McCallum, M Won, S Oramas, E Schmidt arXiv preprint arXiv:2010.11512, 2020 | 17 | 2020 |
Accounting for deterministic noise components in a MMSE STSA speech enhancement framework M McCallum, B Guillemin 2012 International Symposium on Communications and Information Technologies …, 2012 | 7 | 2012 |
Methods and apparatus to adjust audio playback settings R Coover, CA Summers, J Renner, M Cremer, W Mansfield, M McCallum US Patent 11,223,340, 2022 | 5 | 2022 |
Methods and apparatus to adjust audio playback settings based on analysis of audio characteristics R Coover, CA Summers, T Hodges, J Renner, M Cremer, M McCallum US Patent 11,218,125, 2022 | 5 | 2022 |
On the effect of data-augmentation on local embedding properties in the contrastive learning of music audio representations MC McCallum, MEP Davies, F Henkel, J Kim, SE Sandberg ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | 4 | 2024 |
Methods and apparatus to reduce noise from harmonic noise sources M McCallum US Patent 10,726,860, 2020 | 4 | 2020 |
Joint stochastic-deterministic wiener filtering with recursive Bayesian estimation of deterministic speech. MC McCallum, BJ Guillemin Interspeech, 460-464, 2013 | 4 | 2013 |
A novel 1d state space for efficient music rhythmic analysis M Heydari, M McCallum, A Ehmann, Z Duan ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 3 | 2022 |
Similar but faster: manipulation of tempo in music audio embeddings for tempo prediction and search MC McCallum, F Henkel, J Kim, SE Sandberg, MEP Davies ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | 2 | 2024 |
Methods and apparatus to reduce noise from harmonic noise sources M McCallum US Patent 11,017,797, 2021 | 2 | 2021 |
Foreground Harmonic Noise Reduction for Robust Audio Fingerprinting MC McCallum 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 2 | 2018 |
Single-Channel Statistical Bayesian Short-Time Fourier Transform Speech Enhancement with Deterministic A Priori Information M McCallum University of Auckland, 2014 | 2 | 2014 |
Methods and apparatus to segment audio and determine audio segment similarities M McCallum US Patent 11,657,798, 2023 | 1 | 2023 |
Unsupervised Deep Feature Learning for Music Segmentation MC McCallum ISMIR (Late Breaking Session), 2018 | 1 | 2018 |
Stochastic-deterministic signal modelling for the tracking of pitch in noise and speech mixtures using factorial HMMs. MC McCallum, BJ Guillemin INTERSPEECH, 3289-3293, 2013 | 1 | 2013 |