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EMO-KNOW: A Large Scale Dataset on Emotion-Cause.

, , , , and . EMNLP (Findings), page 11043-11051. Association for Computational Linguistics, (2023)

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Genre-Conditioned Acoustic Models for Automatic Lyrics Transcription of Polyphonic Music., , and . ICASSP, page 791-795. IEEE, (2022)Automatic Rank-Ordering of Singing Vocals with Twin-Neural Network., , and . ISMIR, page 416-423. (2020)Sound Model Factory: An Integrated System Architecture for Generative Audio Modelling., , and . EvoMUSART, volume 13221 of Lecture Notes in Computer Science, page 308-322. Springer, (2022)Automatic Evaluation of Singing Quality without a Reference., , and . APSIPA, page 990-997. IEEE, (2018)Exploring the Design Space of Assistive Augmentation., , , , , , , , , and . AHs, page 371-373. ACM, (2023)Automatic Lyrics-to-audio Alignment on Polyphonic Music Using Singing-adapted Acoustic Models., , , and . ICASSP, page 396-400. IEEE, (2019)Semi-supervised Lyrics and Solo-singing Alignment., , , and . ISMIR, page 600-607. (2018)Objective Assessment of Ornamentation in Indian Classical Singing., and . CMMR/FRSM, volume 7172 of Lecture Notes in Computer Science, page 1-25. Springer, (2011)Parameter Sensitivity of Deep-Feature based Evaluation Metrics for Audio Textures., , , , , and . ISMIR, page 462-468. (2022)Towards Controllable Audio Texture Morphing., , , , , and . ICASSP, page 1-5. IEEE, (2023)