publication . Other literature type . Preprint . Conference object . 2018

Multitask Learning for Frame-level Instrument Recognition

Yun-Ning Hung; Yi-An Chen; Yi-Hsuan Yang;
  • Published: 02 Nov 2018
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Abstract
Comment: This is a pre-print version of an ICASSP 2019 paper
Subjects
free text keywords: Computer Science - Sound, Electrical Engineering and Systems Science - Audio and Speech Processing, Music theory, Machine learning, computer.software_genre, computer, Multi-task learning, Musical, Artificial intelligence, business.industry, business, Time frame, Network architecture, Pattern recognition, Computer science, Need to know, Instrument recognition, Polyphony
20 references, page 1 of 2

[7] Eric J. Humphrey, Simon Durand, and Brian McFee, “OpenMIC-2018: An open dataset for multiple instrument recognition,” in Proc. ISMIR, 2018, [Online] https://github.com/cosmir/openmic-2018.

[8] Jort F. Gemmeke et al., “Audio Set: An ontology and human-labeled dataset for audio events,” in Proc. ICASSP, 2017, pp. 776-780. [OpenAIRE]

[9] Zhiyao Duan, Bryan Pardo, and Changshui Zhang, “Multiple fundamental frequency estimation by modeling spectral peaks and non-peak regions,” IEEE Trans. Audio, Speech, and Language Processing, vol. 18, pp. 2121-2133, 2010. [OpenAIRE]

[10] Siddharth Gururani and Alexander Lerch, “Mixing secrets: a multi-track dataset for instrument recognition in polyphonic music,” in Proc. ISMIR-LBD, 2017.

[11] Jong Wook Kim et al., “Crepe: A convolutional representation for pitch estimation,” in Proc. ICASSP, 2018.

[12] Peter Li et al., “Automatic instrument recognition in polyphonic music using convolutional neural networks,” CoRR, vol. abs/1511.05520, 2015.

[13] Siddharth Gururani, Cameron Summers, and Alexander Lerch, “Instrument activity detection in polyphonic music using deep neural networks,” in Proc. ISMIR, 2018.

[14] Yun-Ning Hung and Yi-Hsuan Yang, “Frame-level instrument recognition by timbre and pitch,” in Proc. ISMIR, 2018, pp. 135-142.

[15] Dimitrios Giannoulis, Emmanouil Benetos, Anssi Klapuri, and Mark D. Plumbley, “Improving instrument recognition in polyphonic music through system integration,” Proc. ICASSP, pp. 5222-5226, 2014. [OpenAIRE]

[17] Hao-Wen Dong, Wen-Yi Hsiao, and Yi-Hsuan Yang, “Pypianoroll: Open source Python package for handling multitrack pianoroll,” in Proc. ISMIR-LBD, 2018, [Online] https://github.com/salu133445/pypianoroll.

[18] Zhiyao Duan, Jinyu Han, and Bryan Pardo, “Multi-pitch streaming of harmonic sound mixtures,” IEEE/ACM Trans. Audio, Speech, and Language Processing, vol. 22, no. 1, pp. 138-150, 2014.

[19] Vipul Arora and Laxmidhar Behera, “Multiple f0 estimation and source clustering of polyphonic music audio using PLCA and HMRFs,” IEEE/ACM Trans. Audio, Speech and Language Processing, vol. 23, no. 2, pp. 278-287, 2015.

[20] Colin Raffel, Learning-Based Methods for Comparing Sequences, with Applications to Audio-to-MIDI Alignment and Matching, Ph.D. thesis, Columbia U., 2016, [Online] https://github.com/craffel/alignment-search. [OpenAIRE]

[21] Kyungyun Lee, Keunwoo Choi, and Juhan Nam, “Revisiting singing voice detection: A quantitative review and the future outlook,” in Proc. ISMIR, 2018. [OpenAIRE]

[22] Mathieu Ramona, G. Richard, and B. David, “Vocal detection in music with support vector machines,” in Proc. ICASSP, 2008, pp. 1885-1888. [OpenAIRE]

20 references, page 1 of 2
Abstract
Comment: This is a pre-print version of an ICASSP 2019 paper
Subjects
free text keywords: Computer Science - Sound, Electrical Engineering and Systems Science - Audio and Speech Processing, Music theory, Machine learning, computer.software_genre, computer, Multi-task learning, Musical, Artificial intelligence, business.industry, business, Time frame, Network architecture, Pattern recognition, Computer science, Need to know, Instrument recognition, Polyphony
20 references, page 1 of 2

[7] Eric J. Humphrey, Simon Durand, and Brian McFee, “OpenMIC-2018: An open dataset for multiple instrument recognition,” in Proc. ISMIR, 2018, [Online] https://github.com/cosmir/openmic-2018.

[8] Jort F. Gemmeke et al., “Audio Set: An ontology and human-labeled dataset for audio events,” in Proc. ICASSP, 2017, pp. 776-780. [OpenAIRE]

[9] Zhiyao Duan, Bryan Pardo, and Changshui Zhang, “Multiple fundamental frequency estimation by modeling spectral peaks and non-peak regions,” IEEE Trans. Audio, Speech, and Language Processing, vol. 18, pp. 2121-2133, 2010. [OpenAIRE]

[10] Siddharth Gururani and Alexander Lerch, “Mixing secrets: a multi-track dataset for instrument recognition in polyphonic music,” in Proc. ISMIR-LBD, 2017.

[11] Jong Wook Kim et al., “Crepe: A convolutional representation for pitch estimation,” in Proc. ICASSP, 2018.

[12] Peter Li et al., “Automatic instrument recognition in polyphonic music using convolutional neural networks,” CoRR, vol. abs/1511.05520, 2015.

[13] Siddharth Gururani, Cameron Summers, and Alexander Lerch, “Instrument activity detection in polyphonic music using deep neural networks,” in Proc. ISMIR, 2018.

[14] Yun-Ning Hung and Yi-Hsuan Yang, “Frame-level instrument recognition by timbre and pitch,” in Proc. ISMIR, 2018, pp. 135-142.

[15] Dimitrios Giannoulis, Emmanouil Benetos, Anssi Klapuri, and Mark D. Plumbley, “Improving instrument recognition in polyphonic music through system integration,” Proc. ICASSP, pp. 5222-5226, 2014. [OpenAIRE]

[17] Hao-Wen Dong, Wen-Yi Hsiao, and Yi-Hsuan Yang, “Pypianoroll: Open source Python package for handling multitrack pianoroll,” in Proc. ISMIR-LBD, 2018, [Online] https://github.com/salu133445/pypianoroll.

[18] Zhiyao Duan, Jinyu Han, and Bryan Pardo, “Multi-pitch streaming of harmonic sound mixtures,” IEEE/ACM Trans. Audio, Speech, and Language Processing, vol. 22, no. 1, pp. 138-150, 2014.

[19] Vipul Arora and Laxmidhar Behera, “Multiple f0 estimation and source clustering of polyphonic music audio using PLCA and HMRFs,” IEEE/ACM Trans. Audio, Speech and Language Processing, vol. 23, no. 2, pp. 278-287, 2015.

[20] Colin Raffel, Learning-Based Methods for Comparing Sequences, with Applications to Audio-to-MIDI Alignment and Matching, Ph.D. thesis, Columbia U., 2016, [Online] https://github.com/craffel/alignment-search. [OpenAIRE]

[21] Kyungyun Lee, Keunwoo Choi, and Juhan Nam, “Revisiting singing voice detection: A quantitative review and the future outlook,” in Proc. ISMIR, 2018. [OpenAIRE]

[22] Mathieu Ramona, G. Richard, and B. David, “Vocal detection in music with support vector machines,” in Proc. ICASSP, 2008, pp. 1885-1888. [OpenAIRE]

20 references, page 1 of 2
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publication . Other literature type . Preprint . Conference object . 2018

Multitask Learning for Frame-level Instrument Recognition

Yun-Ning Hung; Yi-An Chen; Yi-Hsuan Yang;