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Novel affective features for multiscale prediction of emotion in music., , , , and . MMSP, page 1-5. IEEE, (2016)Towards Accurate and Real-Time End-of-Speech Estimation., , , , , , and . ICASSP, page 1-5. IEEE, (2023)Noise Aware and Combined Noise Models for Speech Denoising in Unknown Noise Conditions., , and . INTERSPEECH, page 2866-2869. ISCA, (2016)CNMF-based acoustic features for noise-robust ASR., , , and . ICASSP, page 5735-5739. IEEE, (2016)TILES audio recorder: an unobtrusive wearable solution to track audio activity., , , , and . WearSys@MobiSys, page 33-38. ACM, (2018)Affective Feature Design and Predicting Continuous Affective Dimensions from Music., , , , , , and . MediaEval, volume 1263 of CEUR Workshop Proceedings, CEUR-WS.org, (2014)Exploring the Relationship between Conic Affinity of NMF Dictionaries and Speech Enhancement Metrics., , and . INTERSPEECH, page 1146-1150. ISCA, (2018)A two-step technique for MRI audio enhancement using dictionary learning and wavelet packet analysis., , and . INTERSPEECH, page 1312-1315. ISCA, (2013)Learning a speech manifold for signal subspace speech denoising., and . INTERSPEECH, page 1735-1739. ISCA, (2015)Acoustic Denoising Using Dictionary Learning With Spectral and Temporal Regularization., , and . IEEE ACM Trans. Audio Speech Lang. Process., 26 (5): 967-980 (2018)