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My publication sorted by topic

o Music generation

o Music and emotion

o Music/sound classification and auto-tagging

o Source separation

o Music transcription

o Structure analysis

o Performance/expressivity

o Recommendation

o Music and video

o Retrieval

o Editorial

o Others

(NOTE: Please visit here for the alternative version in chronological order)

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Music Generation (back to top)

• Chih-Pin Tan, Shuen-Huei Guan, and Yi-Hsuan Yang,
  “PiCoGen: Generate piano covers with a two-stage approach,”
  in Proc. ACM Int. Conf. Multimedia Retrieval (ICMR),
  short paper, 2024.
  (paper, demo)
• Yu-Hua Chen, Woosung Choi, WeiHsiang Liao, Marco A. Martinez Ramirez, Kin Wai Cheuk, Yi-Hsuan Yang, and Yuki Mitsufuji,
  "Neural amplifier modelling with several GAN variants,"
  Int. Society for Music Information Retrieval Conf. (ISMIR-LBD’23),
  late-breaking and demo paper, 2023.
  (paper)
• Shih-Lun Wu and Yi-Hsuan Yang,
  "Compose & Embellish: Well-structured piano performance generation via a two-stage approach,"
  in Proc. IEEE International Conference on Acoustics, Speech and Signal Processing 2023 (ICASSP’23).
  (paper, code, demo)
• Shih-Lun Wu and Yi-Hsuan Yang,
  "MuseMorphose: Full-song and fine-grained piano music style transfer with just one Transformer VAE,"
  in: IEEE/ACM Transactions on Audio, Speech, and Language Processing (TASLP), vol. 31, pp. 1953-1967, May 2023.
  (paper, code, demo)
• Yueh-Kao Wu, Ching-Yu Chiu, and Yi-Hsuan Yang,
  "JukeDrummer: Conditional beat-aware drum accompaniment generation in the audio domain using Transformer VQ-VAE,"
  in Proc. Int. Society for Music Information Retrieval Conf. 2022 (ISMIR'22), pp. 193-200.
  (paper, demo, code)
• Yen-Tung Yeh, Bo-Yu Chen, and Yi-Hsuan Yang,
  "Exploiting pre-trained feature networks for generative adversarial networks in audio-domain loop generation,"
  in Proc. Int. Society for Music Information Retrieval Conf. 2022 (ISMIR'22).
  (paper, demo, code)
• Chih-Pin Tan, Wen-Yu Su, and Yi-Hsuan Yang,
  "Melody infilling with user-provided structural context,"
  in Proc. Int. Society for Music Information Retrieval Conf. 2022 (ISMIR'22).
  (paper, demo, code)
• Da-Yi Wu, Wen-Yi Hsiao, Fu-Rong Yang, Oscar Friedman, Warren Jackson, Scott Bruzenak, Yi-Wen Liu, and Yi-Hsuan Yang,
  "DDSP-based singing vocoders: A new subtractive-based synthesizer and a comprehensive evaluation,"
  in Proc. Int. Society for Music Information Retrieval Conf. 2022 (ISMIR'22), pp. 76-83.
  (paper, demo, code)
• Chien-Feng Liao, Jen-Yu Liu, and Yi-Hsuan Yang,
  "KaraSinger: Score-free singing voice synthesis with VQ-VAE using Mel-spectrograms,"
  in Proc. IEEE International Conference on Acoustics, Speech and Signal Processing 2022 (ICASSP’22).
  (paper, demo)
• Bo-Yu Chen, Wei-Han Hsu, Wei-Hsiang Liao, Marco A. Martínez Ramírez, Yuki Mitsufuji, and Yi-Hsuan Yang,
  "Automatic DJ transitions with differentiable audio effects and generative adversarial networks,"
  in Proc. IEEE International Conference on Acoustics, Speech and Signal Processing 2022 (ICASSP’22).
  (paper, demo, code)
• Yi-Jen Shih, Shih-Lun Wu, Frank Zalkow, Meinard Müller, and Yi-Hsuan Yang,
  "Theme Transformer: Symbolic music generation with theme-conditioned Transformer,"
  IEEE Transactions on Multimedia (TMM),
  vol. 25, pp. 3495-3508, March 2022.
  (paper, code, demo, video)
• Chih-Pin Tan, Chin-Jui Chang, Alvin W. Y. Su, and Yi-Hsuan Yang,
  "Music score expansion with variable-length infilling,"
  ISMIR demo paper (non-peer reviewed two-page extended abstract) 2021 (ISMIR'21-LBD),
  (paper, demo)
• Joann Ching and Yi-Hsuan Yang,
  "Learning to generate piano music with sustain pedals,"
  ISMIR demo paper (non-peer reviewed two-page extended abstract) 2021 (ISMIR'21-LBD),
  (paper, code, demo)
• Fu-Rong Yang, Yin-Ping Cho, Da-Yi Wu, Yi-Hsuan Yang, Shan-Hung Wu, and Yi-Wen Liu,
  "Mandarin singing voice synthesis with a phonology-based duration model,"
  in Proc. Asia Pacific Signal and Information Processing Association Annual Summit and Conf. 2021 (APSIPA ASC’21),.
  (paper, code, demo)
• Chin-Jui Chang, Chun-Yi Lee, and Yi-Hsuan Yang,
  "Variable-length music score infilling via XLNet and musically specialized positional encoding,"
  in Proc. Int. Society for Music Information Retrieval Conf. 2021 (ISMIR'21).
  (paper, code, demo)
• Tun-Min Hung, Bo-Yu Chen, Yen-Tung Yeh, and Yi-Hsuan Yang,
  "A benchmarking initiative for audio-domain music generation using the FreeSound Loop Dataset,"
  in Proc. Int. Society for Music Information Retrieval Conf. 2021 (ISMIR'21).
  (paper, code, demo)
• Hsiao-Tzu Hung, Joann Ching, Seungheon Doh, Nabin Kim, Juhan Nam and Yi-Hsuan Yang,
  "EMOPIA: A multi-modal pop piano dataset for emotion recognition and emotion-based music generation,"
  in Proc. Int. Society for Music Information Retrieval Conf. 2021 (ISMIR'21).
  (paper, code, code2, database, demo)
• Pedro Sarmento, Adarsh Kumar, C. J. Carr, Zack Zukowski, Mathieu Barthet, and Yi-Hsuan Yang,
  "DadaGP: A dataset of tokenized GuitarPro songs for sequence models,"
  in Proc. Int. Society for Music Information Retrieval Conf. 2021 (ISMIR'21).
  (paper, code, database, demo)
• Antoine Liutkus, Ondřej Cífka, Shih-Lun Wu, Umut Simsekli, Yi-Hsuan Yang, and Gael Richard,
  "Relative positional encoding for Transformers with linear complexity,"
  in Proc. Int. Conf. Machine Learning, long-presentation paper (ICML’21; acceptance rate: 9%), 2021.
  (paper, demo, code)
• Wen-Yi Hsiao, Jen-Yu Liu, Yin-Cheng Yeh, and Yi-Hsuan Yang,
  "Compound Word Transformer: Learning to compose full-song music over dynamic directed hypergraphs,"
  in Proc. AAAI Conf. Artificial Intelligence (AAAI’21; acceptance rate: 21%), 2021.
  (paper, demo, code, poster)
• Yin-Cheng Yeh, Wen-Yi Hsiao, Satoru Fukayama, Tetsuro Kitahara, Benjamin Genchel, Hao-Min Liu, Hao-Wen Dong, Yian Chen, Terence Leong, and Yi-Hsuan Yang,
  "Automatic melody harmonization with triad chords: A comparative study,"
  Journal of New Music Research (JNMR),
  vol. 50, no. 1, pp. 37-51, Feb 2021.
  (paper)
• Yu-Hua Chen, Yu-Siang Huang, Wen-Yi Hsiao, and Yi-Hsuan Yang,
  "Automatic composition of guitar tabs by Transformers and groove modeling,"
  in Proc. Int. Society for Music Information Retrieval Conf. 2020 (ISMIR'20).
  (paper, demo)
• Shih-Lun Wu and Yi-Hsuan Yang,
  "The Jazz Transformer on the front line: Exploring the shortcomings of AI-composed music through quantitative measures,"
  in Proc. Int. Society for Music Information Retrieval Conf. 2020 (ISMIR'20).
  (paper, demo, code1, code2)
• Bo-Yu Chen, Jordan Smith, and Yi-Hsuan Yang,
  "Neural loop combiner: Neural network models for assessing the compatibility of loops,"
  in Proc. Int. Society for Music Information Retrieval Conf. 2020 (ISMIR'20).
  (paper, demo, code, data)
• Antonio Ramires, Frederic Font, Dmitry Bogdanov, Jordan Smith, Yi-Hsuan Yang, Joann Ching, Bo-Yu Chen, Yueh-Kao Wu, Hsu Wei-Han, and Xavier Serra,
  "The Freesound Loop Dataset and annotation tool,"
  in Proc. Int. Society for Music Information Retrieval Conf. 2020 (ISMIR'20).
  (paper, code, data)
• Jen-Yu Liu, Yu-Hua Chen, Yin-Cheng Yeh and Yi-Hsuan Yang,
  "Unconditional audio generation with generative adversarial networks and cycle regularization,"
  in Proc. INTERSPEECH 2020 (INTERSPEECH’20).
  (paper, code)
• Da-Yi Wu and Yi-Hsuan Yang,
  "Speech-to-singing conversion based on boundary equilibrium GAN,"
  in Proc. INTERSPEECH 2020 (INTERSPEECH’20).
  (paper, code, demo)
• Yu-Siang Huang and Yi-Hsuan Yang,
  "Pop Music Transformer: Beat-based modeling and generation of expressive Pop piano compositions,"
  in Proc. ACM Multimedia (MM’20).
  (paper, demo, code).
• Jayneel Parekh, Preeti Rao, and Yi-Hsuan Yang,
  "Speech-to-singing conversion in an encoder-decoder framework,"
  in Proc. IEEE International Conference on Acoustics, Speech and Signal Processing 2020 (ICASSP’20)
  (paper, demo, code).
• Jen-Yu Liu, Yu-Hua Chen, Yin-Cheng Yeh, and Yi-Hsuan Yang,
  "Score and lyrics-free singing voice generation,"
  in Proc. Int. Conf. Computational Creativity (ICCC’20).
  (paper)
• Wen-Yi Hsiao, Yin-Cheng Yeh, Yu-Siang Huang, Chung-Yang Wang, Jen-Yu Liu, Tsu-Kuang Hsieh, Hsiao-Tzu Hung, Jun-Yuan Wang, and Yi-Hsuan Yang,
  "Jamming with Yating: Interactive demonstration of a music composition AI,"
  ISMIR demo paper (non-peer reviewed two-page extended abstract) 2019 (ISMIR'19-LBD),
  (paper, demo)
• Yin-Cheng Yeh, Jen-Yu Liu, Wen-Yi Hsiao, Yu-Siang Huang, and Yi-Hsuan Yang,
  "Learning to generate Jazz and Pop piano music from audio via MIR techniques,"
  ISMIR demo paper (non-peer reviewed two-page extended abstract) 2019 (ISMIR'19-LBD),
  (paper, demo)
• Hsiao-Tzu Hung, Chung-Yang Wang, Yi-Hsuan Yang, Hsin-Min Wang,
  "Improving automatic Jazz melody generation by transfer learning techniques,"
  in Proc. Asia Pacific Signal and Information Processing Association Annual Summit and Conf. 2019 (APSIPA ASC’19),
  (paper, demo)
• Frederic Tamagnan and Yi-Hsuan Yang,
  "Drum fills detection and generation,"
  in Proc. Int. Symp. Computer Music Multidisciplinary Research 2019 (CMMR’19).
  (paper, demo)
• Yun-Ning Hung, I-Tung Chiang, Yi-An Chen, and Yi-Hsuan Yang
  "Musical composition style transfer via disentangled timbre representations,"
  in Proc. Int. Joint Conf. Artificial Intelligence 2019 (IJCAI’19; acceptance rate: 17.9%),
  (paper, demo, code)
• Yu-Hua Chen, Bryan Wang and Yi-Hsuan Yang,
  "Demonstration of PerformanceNet: A convolutional neural network model for score-to-audio music generation,"
  in Proc. Int. Joint Conf. Artificial Intelligence 2019 (IJCAI’19), demo paper,
  (paper, demo, code)
• Hao-Wen Dong and Yi-Hsuan Yang,
  "Towards a deeper understanding of adversarial losses,"
  in ArXiv e-prints, abs/1901.08753, January 2019.
  (paper, code)
• Vibert Thio, Hao-Min Liu, Yin-Cheng Yeh, and Yi-Hsuan Yang,
  "A minimal template for interactive web-based demonstrations of musical machine learning,"
  in Proc. Workshop on Intelligent Music Interfaces for Listening and Creation 2019 (MILC’19)
  (paper, code)
• Bryan Wang and Yi-Hsuan Yang,
  "PerformanceNet: Score-to-audio music generation with multi-band convolutional residual network,"
  in Proc. AAAI Conf. Artificial Intelligence (AAAI’19; acceptance rate: 16.2%), 2019.
  (paper, demo, code, bib)
• Hao-Min Liu and Yi-Hsuan Yang,
  "Lead sheet generation and arrangement by conditional generative adversarial network,"
  in Proc. IEEE Int. Conf. Machine Learning and Applications (ICMLA’18).
  (paper, demo, code, code2, code3)
• Hao-Min Liu, Meng-Hsuan Wu and Yi-Hsuan Yang,
  "Lead sheet generation and arrangement via a hybrid generative model,"
  ISMIR demo paper (non-peer reviewed two-page extended abstract) 2018 (ISMIR'18-LBD).
  (paper, code)
• Hao-Wen Dong, Wen-Yi Hsiao and Yi-Hsuan Yang,
  "Pypianoroll: Open source Python package for handling multitrack pianorolls,"
  ISMIR demo paper (non-peer reviewed two-page extended abstract) 2018 (ISMIR'18-LBD).
  (paper, code)
• Hao-Wen Dong and Yi-Hsuan Yang,
  "Training generative adversarial networks with binary neurons by end-to-end backpropagation,"
  in ArXiv e-prints, abs/1810.04714, October 2018.
  (paper, code, press)
• Cheng-Wei Wu, Jen-Yu Liu, Yi-Hsuan Yang, Jyh-Shing R. Jang,
  "Singing style transfer using cycle-consistent boundary equilibrium generative adversarial networks,"
  in Proc. Joint Workshop on Machine Learning for Music, extended abstract, 2018.
  (paper, demo)
• Hao-Wen Dong and Yi-Hsuan Yang,
  "Convolutional generative adversarial networks with binary neurons for polyphonic music generation,"
  in Proc. Int. Society for Music Information Retrieval Conf. 2018 (ISMIR'18).
  (paper, demo, code, slides, arxiv, bib)
• Hao-Wen Dong, Wen-Yi Hsiao, Li-Chia Yang, and Yi-Hsuan Yang,
  "MuseGAN: Multi-track sequential generative adversarial networks for symbolic music generation and accompaniment,"
  in Proc. AAAI Conf. Artificial Intelligence (AAAI’18), 2018.
  (paper, demo, code, data, bib)
• Hao-Wen Dong, Wen-Yi Hsiao, Li-Chia Yang, and Yi-Hsuan Yang,
  "MuseGAN: Demonstration of a convolutional GAN based model for generating multi-track piano-rolls,"
  ISMIR demo paper (non-peer reviewed two-page extended abstract) 2017 (ISMIR'17-LBD).
  (paper, demo)
• Li-Chia Yang, Szu-Yu Chou, and Yi-Hsuan Yang,
  "MidiNet: A convolutional generative adversarial network for symbolic-domain music generation,"
  in Proc. Int. Society for Music Information Retrieval Conf. 2017 (ISMIR'17), pp. 324-331.
  (paper, demo, code, bib)
• Shih-Yang Su, Cheng-Kai Chiu, Li Su, and Yi-Hsuan Yang,
  "Automatic conversion of pop music into chiptunes for 8-bit pixel art,"
  in Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing 2017 (ICASSP’17), accepted.
  (paper, bib) [project webpage (+demo +code)]

Music and Emotion (back to top)

• Juan Sebastián Gomez-Cañón, Estefanía Cano, Tuomas Eerola, Perfecto Herrera, Xiao Hu, Yi-Hsuan Yang, and Emilia Gómez,
  "Music Emotion Recognition: Towards new robust standards in personalized and context-sensitive applications,"
  IEEE Signal Processing Magazine (SPM), vol. 38, no. 6, pp. 106-114, Nov. 2021.
  (paper, repo)
• Eva Zangerle, Chih-Ming Chen, Ming-Feng Tsai and Yi-Hsuan Yang,
  "Leveraging affective hashtags for ranking music recommendations,"
  IEEE Transactions on Affective Computing (TAC),
  vol. 12, no. 1, pp. 78-91, 2021.
  (paper, bib)
• Juan Gómez-Cañón, Estefania Cano, Yi-Hsuan Yang, Perfecto Herrera, and Emilia Gomez,
  "Let's agree to disagree: Consensus entropy active learning for personalized music emotion recognition,"
  in Proc. Int. Society for Music Information Retrieval Conf. 2021 (ISMIR'21).
  (paper, code)
• Jianyu Fan, Yi-Hsuan Yang, Kui Dong, and Philippe Pasquier,
  "A comparative study of Western and Chinese classical music based on soundscape models,"
  in Proc. IEEE International Conference on Acoustics, Speech and Signal Processing 2020 (ICASSP’20)
  (paper, data).
• Hsiao-Tzu Hung, Yu-Hua Chen, Maximilian Mayerl, Michael Vötter, Eva Zangerle, and Yi-Hsuan Yang,
  "MediaEval 2019 emotion and theme recognition task: A VQ-VAE based approach,"
  MediaEval working note paper 2019 (MediaEval’19).
  (paper, code)
• Maximilian Mayerl, Michael Vötter, Hsiao-Tzu Hung, Bo-Yu Chen, Yi-Hsuan Yang, and Eva Zangerle,
  "Recognizing song mood and theme using convolutional recurrent neural networks,"
  MediaEval working note paper 2019 (MediaEval’19).
  (paper, code)
• Y.-H. Chin, J.-C. Wang, J.-C. Wang and Y.-H. Yang,
  "Predicting the probability density function of music emotion using emotion space mapping,"
  IEEE Transactions on Affective Computing (TAC),
  vol. 9, no. 4, pp. 541-549, Oct.-Dec. 2018.
  (paper, bib)
• Yi-Wei Chen, Yi-Hsuan Yang, and Homer H. Chen,
  "Cross-cultural music emotion recognition by adversarial discriminative domain adaptation,"
  in Proc. IEEE Int. Conf. Machine Learning and Applications (ICMLA’18).
  (paper, code)
• X. Hu and Y.-H. Yang,
  "The mood of Chinese pop music: Representation and recognition,"
  Journal of the Association for Information Science and Technology (JAIST),
  vol. 68, no. 8, August 2017, DOI: 10.1002/asi.23813.
  (paper, bib)
• X. Hu and Y.-H. Yang,
  "Cross-dataset and cross-cultural music mood prediction: A case on Western and Chinese pop songs,"
  IEEE Transactions on Affective Computing (TAC),
  vol. 8, no. 2, pp. 228-240, Apr. 2017.
  (paper, bib)
• Y.-A. Chen, J.-C. Wang, Y.-H. Yang, H.-H. Chen,
  "Component tying for mixture model adaptation in personalization of music emotion recognition,"
  IEEE/ACM Transactions on Audio, Speech, and Language Processing (TASLP),
  vol. 25, no. 7, pp. 1409-1420, Jul. 2017. (a figure of this paper was selected as the cover of this issue)
  (paper, bib)
• A. Aljanaki, Y.-H. Yang, and M. Soleymani,
  "Developing a benchmark for emotional analysis of music,"
  PLOS ONE,
  vol, 12, no. 3, e0173392.doi:10.1371/journal.pone.0173392, Mar. 2017.
  (paper, bib)

· Yuan-Pin Lin, Ping-Keng Jao, and Yi-Hsuan Yang,
"Improving cross-day EEG-based emotion classification using robust principal component analysis,"
Frontiers in Computational Neuroscience (FCN),
2017.
(paper, bib)

• J.-C. Wang, Y.-H. Yang and H.-M. Wang,
  "Affective music information retrieval,"
  in Emotions and Personality in Personalized Services, M. Tkalčič et al, editors,
  Springer International Publishing, 2016
  (link)
• Y.-H. Yang, J.-C. Wang, Y.-A. Chen, and H. H. Chen,
  "Model Adaptation for Personalized Music Emotion Recognition,"
  in Handbook of Pattern Recognition and Computer Vision, C.-H. Chen, editor,
  World Scientific Publishing, Feb. 2016
  (link)
• Y.-H. Yang and Y.-C. Teng,
  "Quantitative study of music listening behavior in a smartphone context,"
  ACM Transactions on Interactive Intelligent Systems (TiiS),
  vol. 5, no. 3, article 14, Aug. 2015.
  (paper, bib, online appendix)
• M. Soleymani, Y.-H. Yang, G. Irie, and A. Hanjalic,
  "Challenges and Perspectives for Affective Analysis in Multimedia,"
  IEEE Transactions on Affective Computing (TAC),
  vol. 6, no. 3, pp. 206-208, Jul.-Sept., 2015
  (paper, bib).
• J.-C. Wang, Y.-H. Yang, H.-M. Wang, and S.-K. Jeng,
  "Modeling the affective content of music with a Gaussian mixture model,"
  IEEE Transactions on Affective Computing (TAC),
  vol. 6, no. 1, pp. 56-68, Feb 2015.
  (paper, bib, code)
• P.-K. Jao, Y.-P. Lin, Y.-H. Yang, and T.-P. Jung,
  "Using robust principal component analysis to alleviate day-to-day variability in EEG based emotion classification,"
  in Proc. Annual Int. Conf. IEEE Engineering in Medicine and Biology Society 2015 (EMBC’15), pp. 570-573.
  (paper)
• A. Aljanaki, Y.-H. Yang, and M. Soleymani,
  "Musical emotion variation detection from acoustic content - lessons learned from developing MediaEval "Emotion in Music" benchmark,"
  in Proc. Int. Conf. Music and Emotion 2015 (ICME4).
  (paper)
• J.-W. Peng, S.-W. Sun, W.-H. Cheng, and Y.-H. Yang,
  "eMosic: Mobile media pushing through social emotion sensing,"
  in Proc. ACM Multimedia 2015 (MM’15), demo paper.
• Y.-A. Chen, Y.-H. Yang, J.-C. Wang and H.-H. Chen,
  "The AMG1608 dataset for music emotion recognition,"
  in Proc. IEEE International Conference on Acoustics, Speech and Signal Processing 2015 (ICASSP’15), pp. 693-697.
  (paper, data)
• M. Soleymani, A. Aljanaki, Y.-H. Yang, M. N. Caro, F. Eyben, K. Markov, B. Schuller, R. Veltkamp, F. Weninger, and F. Wiering,
  "Emotional analysis of music: A comparison of methods,"
  in Proc. ACM Multimedia, short paper (MM’14), pp. 1161-1164.
  (paper, data)
• A. Aljanaki, Y.-H. Yang, and M. Soleymani,
  "Emotion in Music Task at MediaEval 2014,"
  in Proc. MediaEval Workshop (MediaEval’14), extended abstract.
  (paper)
• X. Hu and Y.-H. Yang,
  "Cross-cultural mood regression for music digital libraries,"
  in Proc. IEEE/ACM Joint Conf. Digital Libraries 2014 (DL’14).
  (paper)
• X. Hu and Y.-H. Yang,
  "A study on cross-cultural and cross-dataset generalizability of music mood regression models,"
  in Proc. Sound and Music Computing Conf. 2014 (SMC’14), pp. 1149-1155.
  (paper)
• J.-Y. Liu, S.-Y. Liu and Y.-H. Yang,
  "LJ2M Dataset: Toward better understanding of music listening behavior and user mood,"
  IEEE Int. Conf. Multimedia and Expo. 2014 (ICME’14).
  (paper, data)
• Y.-A. Chen, J.-C. Wang, Y.-H. Yang and H.-H. Chen,
  "Linear regression-based adaptation of music emotion recognition models for personalization,"
  IEEE International Conference on Acoustics, Speech and Signal Processing 2014 (ICASSP’14), pp. 2149-2153.
  (paper)
• Y.-P. Lin, Y.-H. Yang, and T.-P. Jung
  "Fusion of Electroencephalogram dynamics and musical contents for estimating emotional responses in music listening,"
  Frontiers in Neuroscience,
  vol. 8, no. 94, pp. 1-14, May 2014.
  (paper, bib)
• Y.-H. Yang and J.-Y. Liu,
  "Quantitative study of music listening behavior in a social and affective context,"
  Special Issue on Social Media as Sensors,
  IEEE Transactions on Multimedia (TMM),
  vol. 15, no. 6, pp. 1304-1315, Oct. 2013.
  (paper, data, bib)
• K.-S. Lin, A. Lee, Y.-H. Yang, C.-T. Lee, and H.-H. Chen,
  "Automatic highlights extraction for drama video using music emotion and human face features,"
  Neurocomputing (NEUCOM), Elsevier,
  vol. 119, pp. 111-117, Nov. 2013,.
  (paper, bib)
• M. Soleymani, M. N. Caro, E. Schmidt, C.-Y. Sha, and Y.-H. Yang,
  "The MediaEval 2013 brave new task: Emotion in Music,"
  in Proc. MediaEval Workshop (MediaEval’13), in conjunction with ACM Multimedia, extended abstract.
  (paper, data)
• M. Soleymani, M. N. Caro, E. Schmidt, C.-Y. Sha, and Y.-H. Yang,
  "1000 songs for emotional analysis of music."
  in Proc. Int. Workshop on Crowdsourcing for Multimedia 2013 (CrowdMM'13), in conjunction with ACM Multimedia (MM), pp. 1-6.
  (paper, data)
• Y.-H. Yang and H.-H. Chen,
  "Machine recognition of music emotion: A review,"
  ACM Transactions on Intelligent Systems and Technology (TIST),
  vol. 3, no. 3, May 2012.
  (paper, bib)
• J.-C. Wang, Y.-H. Yang, H.-M. Wang, and S.-K. Jeng,
  "Personalized music emotion recognition via model adaptation,"
  in Proc. Asia Pacific Signal and Information Processing Association Annual Summit and Conf. 2012 (APSIPA ASC'12).
  (paper)
• J.-C. Wang, Y.-H. Yang, H.-M. Wang, and S.-K. Jeng,
  "The Acoustic Emotion Gaussians model for emotion-based music annotation and retrieval,"
  in Proc. ACM Multimedia 2012 (MM'12), full paper (acceptance rate 21%), pp. 89-98.
  (paper, bib, code)
• J.-C. Wang, Y.-H. Yang, K.-C. Chang, H.-M. Wang, and S.-K. Jeng,
  "Exploring the relationship between categorical and dimensional emotion semantics of music,"
  in Int. Workshop on Music Information Retrieval with User-Centered and Multimodal Strategies (MIRUM'12), in conjunction with ACM Multimedia (MM), pp. 63-68.
  (paper)
• Y.-H. Yang and X. Hu,
  "Cross-cultural music mood classification: A comparison of English and Chinese songs,"
  in Proc. Int. Society for Music Information Retrieval 2012 (ISMIR'12), pp. 19-24.
  (paper)
• Y.-C. Lin, Y.-H. Yang and H.-H. Chen,
  "Exploiting online tags for music emotion classification,"
  Special Issue on Social Media,
  ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP),
  vol. 7S, no. 1, Oct. 2011.
  (paper, bib)
• Y.-H. Yang and H.-H. Chen,
  "Prediction of the distribution of perceived music emotions using discrete samples,"
  IEEE Transactions on Audio, Speech and Language Processing (TASLP),
  vol. 19, no. 7, pp. 2184-2196, Sept. 2011.
  (paper, bib) [project page]
• Y.-H. Yang and H.-H. Chen,
  "Ranking-based emotion recognition for music organization and retrieval,"
  IEEE Transactions on Audio, Speech and Language Processing (TASLP),
  vol. 19, no. 4, pp. 762-774, May 2011.
  (paper, bib) [project page]
• Y.-H. Yang and H.-H. Chen,
  Music Emotion Recognition,
  CRC Taylor & Francis Books, Feb. 2011
  (link, bib)
• Y.-H. Yang and H.-H. Chen,
  "Searching music in the emotion plane,"
  IEEE MMTC E-Letter, November issue, 2009, invited paper.
  (paper)
• Y.-H. Yang, Y.-C. Lin, and H.-H. Chen,
  "Personalized music emotion recognition,"
  in Proc. ACM Int. Conf. Information Retrieval 2009 (SIGIR'09), Boston, USA, short paper, pp. 748-749.
  (paper)
• Y.-H. Yang and H.-H. Chen,
  "Music emotion ranking,"
  in Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing 2009 (ICASSP'09), Taipei, Taiwan, pp. 1657-1660.
  (paper, abstract) [project page, include dataset]
• Y.-C. Lin, Y.-H. Yang, H.-H. Chen, I-Bin Liao, and Yeh-Chin Ho
  "Exploiting genre for music emotion classification,"
  in Proc. IEEE Int. Conf. Multimedia and Expo. 2009 (ICME'09), New York, USA, pp. 618-621.
  (paper) [project page, include dataset]
• Y.-H. Yang, Y.-C. Lin, H.-T. Cheng, and H.-H. Chen,
  "Mr.Emo: Music retrieval in the emotion plane,"
  in Proc. ACM Multimedia 2008 (MM'08) (demonstration), pp. 1003-1004.
  (paper, demo)
• T.-L. Wu et al,
  "Interactive content presenter based on expressed emotion and physiological feedback,"
  in Proc. ACM Multimedia 2008 (MM'08) (demonstration), pp. 1009-1010.
  (paper, demo)
• Y.-H. Yang, Y.-C. Lin, H.-T. Cheng, I.-B. Liao, Yeh-Chin Ho, and H.-H. Chen,
  "Toward multi-modal music emotion classification,"
  in Proc. Pacific-Rim Conf. Multimedia 2008 (PCM'08), pp. 70-79.
  (paper, slides)

• Y.-H. Yang, Y.-F. Su, Y.-C. Lin, and H.-H. Chen,
  "Music emotion recognition: The role of individuality,"
  in Proc. ACM SIGMM Int. Workshop on Human-centered Multimedia 2007, in conjunction with ACM Multimedia (ACM MM/HCM'07), Augsburg, Germany, pp. 13-21.
  (paper, slides) [project page(include dataset and the software 'AnnoEmo')]
• Y.-H. Yang, Y.-C. Lin, Y.-F. Su, and H.-H. Chen,
  "A regression approach to music emotion recognition,"
  IEEE Transactions on Audio, Speech and Language Processing (TASLP),
  vol. 16, no. 2, pp. 448-457, Feb. 2008. (IEEE Signal Processing Society Young Author Best Paper Award)
  (paper, slides, bib) [project page, include dataset]
• Y.-H. Yang, Y.-C. Lin, Y.-F. Su, and H.-H. Chen,
  "Music emotion classification: A regression approach,"
  in Proc. IEEE Int. Conf. Multimedia and Expo. 2007 (ICME'07), Bejing, China, pp. 208-211.
  (paper, poster) [project page(include dataset)]

• Y.-H. Yang, C.-C Liu, and H.-H. Chen,
  "Music emotion classification: A fuzzy approach,"
  in Proc. ACM Multimedia 2006 (ACM MM'06), Santa Barbara, CA, USA, pp. 81-84. (short paper)(with travel grant)
  (paper) [project page]
• C.-C Liu, Y.-H. Yang, P.-H. Wu, and H.-H. Chen,
  "Detecting and classifying emotion in popular music,"
  in Proc. 9th Joint Int. Conf. Information Sciences / 7th Int. Conf. Computer Vision, Pattern Recognition and Image Processing 2006 (JCIS/CVPRIP'06), Kaohsiung, Taiwan, pp. 996-999.
  (paper)

Music/sound Classification and Auto-tagging (back to top)

• Yi-Hui Chou, I-Chun Chen, Chin-Jui Chang, Joann Ching, and Yi-Hsuan Yang,
  "MidiBERT-Piano: BERT-like Pre-training for Symbolic Piano Music Classification Tasks,"
  Journal of Creative Music Systems (JCMS),
  accepted for publication, 2024.
  (paper, code, data)
• Wei-Han Hsu, Bo-Yu Chen, and Yi-Hsuan Yang,
  "Deep learning based EDM subgenre classification using Mel-spectrogram and tempogram features,"
  in ArXiv e-prints, abs/2110.08862, October 2021.
  (paper, code)
• Joann Ching, Antonio Ramires, and Yi-Hsuan Yang,
  "Instrument role classification: Auto-tagging for loop based music,"
  in Proc. Joint Conference on AI Music Creativity 2020
  (paper, data)
• Tsung-Han Hsieh, Kai-Hsiang Cheng, Zhe-Cheng Fan, Yu-Ching Yang, and Yi-Hsuan Yang,
  "Addressing the confounds of accompaniments in singer identification,"
  in Proc. IEEE International Conference on Acoustics, Speech and Signal Processing 2020 (ICASSP’20)
  (paper, code).
• Juhan Nam, Keunwoo Choi, Jongpil Lee, Szu-Yu Chou, and Yi-Hsuan Yang,
  "Deep learning for audio-based music classification and tagging,"
  IEEE Signal Processing Magazine (SPM),
  vol. 36, no. 1, pp. 41-51, Jan 2019.
  (paper, bib)
• Kai-Hsiang Cheng, Szu-Yu Chou, and Yi-Hsuan Yang,
  "Multi-label few-shot learning for sound event recognition,"
  in Proc. IEEE Int. Workshop on Multimedia Signal Processing 2019 (MMSP’19), accepted.
  (paper)
• Eva Zangerle, Michael Vötter, Ramona Huber, and Yi-Hsuan Yang,
  "Hit song prediction: Leveraging low- and high-level audio features,"
  in Proc. Int. Society for Music Information Retrieval 2019 (ISMIR'19), pp. 319-326.
  (paper) [project webpage]
• Szu-Yu Chou, Kai-Hsiang Cheng, Jyh-Shing Roger Jang, and Yi-Hsuan Yang,
  "Learning to match transient sound events using attentional similarity for few-shot sound recognition,"
  in Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing 2019 (ICASSP’19), pp. 26-30.
  (paper, code)
• Szu-Yu Chou, Jyh-Shing Roger Jang, and Yi-Hsuan Yang,
  "Learning to recognize transient sound events using attentional supervision,"
  in Proc. Int. Joint Conf. Artificial Intelligence 2018 (IJCAI’18), pp. 3336-3342.
  (paper, code)
• Lang-Chi Yu, Yi-Hsuan Yang, Yun-Ning Hung, Yi-An Chen,
  "Hit song prediction for pop music by Siamese CNN with ranking loss,"
  in ArXiv e-prints, abs/1710.10814, Oct 2017.
  (paper)
• Szu-Yu Chou, Jyh-Shing Roger Jang, and Yi-Hsuan Yang,
  "FrameCNN: A weakly-supervised learning framework for frame-wise acoustic event detection and classification,"
  in Proc. Detection and Classification of Acoustic Scenes and Events Workshop 2017 (DCASE’17), extended abstract.
  (paper)
• Li-Chia Yang, Szu-Yu Chou, Jen-Yu Liu, Yi-Hsuan Yang, and Yi-An Chen,
  "Revisiting the problem of audio-based hit song prediction using convolutional neural networks,"
  in Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing 2017 (ICASSP’17).
  (paper) [project webpage]
• Ting-Wei Su, Jen-Yu Liu, and Yi-Hsuan Yang,
  "Weakly-supervised audio event detection using event-specific Gaussian filters and fully convolutional networks,"
  in Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing 2017 (ICASSP’17).
  (paper) [project webpage]
• J.-Y. Liu, S.-K. Jeng, and Y.-H. Yang,
  "Applying topological persistence in convolutional neural network for music audio signals,"
  in ArXiv e-prints, abs/1608.07373, Aug 2016.
  (paper)
• J.-Y. Liu and Y.-H. Yang,
  "Event localization in music auto-tagging,"
  in Proc. ACM Multimedia 2016, (MM’16), (full paper, acceptance rate=20%), pp. 1048-1057.
  (paper, code, demo, bib)
• P.-K. Jao and Y.-H. Yang,
  "Music annotation and retrieval using unlabeled exemplars: correlation and sparse code,"
  IEEE Signal Processing Letters (SPL),
  vol. 22, no. 10, pp. 1771-1775, Oct. 2015
  (paper, bib).
• L. Su, H.-M. Lin, and Y.-H. Yang,
  "Sparse modeling of magnitude and phase-derived spectra for playing technique classification,"
  IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP),
  vol. 22, no. 12, pp. 2122-2132, Dec. 2014.
  (paper, bib)
• L. Su, C.-C. M. Yeh, J.-Y. Liu, J.-C. Wang, and Y.-H. Yang,
  "A systematic evaluation of the bag-of-frames representation for music information retrieval,"
  Special Issue on Music Data Mining,
  IEEE Transactions on Multimedia (TMM),
  vol. 16, no. 5, pp. 1188-1200, Aug. 2014.
  (paper, bib)
• C.-C. M. Yeh, P.-K. Jao, and Y.-H. Yang,
  "AWtoolbox: Characterizing audio information using audio words,"
  in Proc. ACM Multimedia 2014, short paper (MM’14), pp. 809-812.
  (paper, code)
• S.-Y. Wang, J.-C. Wang, Y.-H. Yang and H.-M. Wang,
  "Towards time-varying music auto-tagging based on CAL500 Expansion,"
  IEEE Int. Conf. Multimedia and Expo. 2014 (ICME’14).
  (paper, data)
• P.-K. Jao, C.-C. M. Yeh and Y.-H. Yang,
  "Modified LASSO screening for audio word-based music classification using large-scale dictionary,"
  IEEE International Conference on Acoustics, Speech and Signal Processing 2014 (ICASSP’14), pp. 5207-5211.
  (paper)
• L.-F. Yu, L. Su and Y.-H. Yang,
  "Sparse cepstral codes and power scale for instrument identification,"
  IEEE International Conference on Acoustics, Speech and Signal Processing 2014 (ICASSP’14), pp. 7460-7464.
  (paper)
• C.-C. M. Yeh, J.-C. Wang, Y.-H. Yang and H.-M. Wang,
  "Improving music auto-tagging by intra-song instance bagging,"
  IEEE International Conference on Acoustics, Speech and Signal Processing 2014 (ICASSP’14), pp. 2139-2143.
  (paper)
• L. Su and Y.-H. Yang,
  "Sparse modeling for artist identification: Exploiting phase information and vocal separation,"
  in Proc. Int. Society for Music Information Retrieval 2013 (ISMIR'13), pp. 349-354.
  (paper)
• P.-K. Jao, L. Su, and Y.-H. Yang,
  "Analyzing the dictionary properties and sparsity constraints for a dictionary-based music genre classification system,"
  in Proc. Asia Pacific Signal and Information Processing Association Annual Summit and Conf. (APSIPA ASC’13), 2013.
  (paper)
• C.-C. Yeh and Y.-H. Yang,
  "Towards a more efficient sparse coding based audio-word feature extraction system,"
  in Proc. Asia Pacific Signal and Information Processing Association Annual Summit and Conf. (APSIPA ASC’13), 2013.
  (paper)
• Y.-H. Yang,
  "Towards real-time music auto-tagging using sparse features,"
  in Proc. IEEE Int. Conf. Multimedia and Expo. 2013 (ICME'13), oral (top 13%), best paper candidate.
  (paper, data)
• C.-C. Yeh, L. Su, and Y.-H. Yang,
  "Dual-layer bag-of-frames model for music genre classification,"
  in Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing 2013 (ICASSP'13).
  (paper)
• C.-Y. Sha, Y.-H. Yang, Y.-C. Lin, and H. H. Chen,
  "Singing voice timbre classification of Chinese popular music,"
  in Proc. IEEE Int. Conf. Acoustics, Speech, and Signal Processing 2013 (ICASSP'13).
  (paper)
• J.-Y. Liu, C.-C. Yeh, Y.-C. Teng, and Y.-H. Yang,
  "Bilingual analysis of song lyrics and audio words,"
  in Proc. ACM Multimedia 2012 (MM'12), short paper, pp. 829-832.
  (paper)
• C.-C. Yeh and Y.-H. Yang,
  "Supervised dictionary learning for music genre classification,"
  in Proc. ACM International Conference on Multimedia Retrieval 2012 (ICMR'12), eight pages.
  (paper)
• Y.-H. Yang, D. Bogdanov, P. Herrera, and M. Sordo,
  "Music retagging using label propagation and robust principal component analysis,"
  in Int. Workshop on Advances in Music Information Research (AdMIRe'12), in conjunction with Int. World Wide Web Conference (WWW), pp. 869-876.
  (paper)
• Y.-H. Kuo, H.-T. Lin, W.-H. Cheng, Y.-H. Yang, and W.-H. Hsu,
  "Unsupervised auxiliary visual words discovery for large-scale image object retrieval,"
  in Proc. ACM Int. Conf. Computer Vision and Pattern Recognition 2011 (CVPR'11).
  (paper)
• Y.-H. Kuo, Y.-L. Wu, K.-T. Chen, Y.-H. Yang, T.-H. Chiu, and W.-H. Hsu,
  "A technical demonstration of large-scale image object retrieval by efficient query evaluation and effective auxiliary visual feature discovery,"
  in Proc. ACM Int. Conf. Multimedia 2010 (MM'10), technical demonstration.
  (paper)
• Y.-H. Yang, Y.-C. Lin, A. Lee, and H.-H. Chen,
  "Improving musical concept detection by ordinal regression and context fusion,"
  in Proc. Int. Society for Music Information Retrieval 2009 (ISMIR'09), pp. 147-152.
  (paper, poster)

Source Separation (back to top)

· Ching-Yu Chiu, Wen-Yi Hsiao, Yin-Cheng Yeh, Yi-Hsuan Yang, and Alvin W. Y. Su,
"Mixing-specific data augmentation techniques for improved blind violin/piano source separation,"
in Proc. IEEE Int. Workshop on Multimedia Signal Processing 2020 (MMSP’20),
(paper, code, demo)

• Jen-Yu Liu and Yi-Hsuan Yang,
  "Dilated convolution with dilated GRU for music source separation,"
  in Proc. Int. Joint Conf. Artificial Intelligence 2019 (IJCAI’19; acceptance rate: 17.9%),
  (paper).
• Jen-Yu Liu and Yi-Hsuan Yang,
  "Denoising auto-encoder with recurrent skip connections and residual regression for music source separation,"
  in Proc. IEEE Int. Conf. Machine Learning and Applications (ICMLA’18).
  (paper, demo)
• T.-S. Chan and Y.-H. Yang,
  "Informed group-sparse representation for singing voice separation,"
  IEEE Signal Processing Letters (SPL),
  vol. 24, no. 2, pp. 156-160, Feb. 2017.
  (paper, bib)
• T.-S. Chan and Y.-H. Yang,
  "Polar n-complex and n-bicomplex singular value decomposition and principal component pursuit,"
  IEEE Transactions on Signal Processing (TSP),
  vol. 64, no. 24, pp. 6533-6544, Dec. 2016 .
  (paper, code, bib)
• P.-K. Jao, L. Su, Y.-H. Yang and B. Wohlberg,
  "Monaural music source separation using convolutional sparse coding,"
  IEEE/ACM Transactions on Audio, Speech, and Language Processing (TASLP),
  vol. 24, no. 11, pp. 2158-2170, Nov. 2016.
  (paper, code, bib) [project page]
• T.-S. Chan and Y.-H. Yang,
  "Complex and quaternionic principal component pursuit and its application to audio separation,"
  IEEE Signal Processing Letters (SPL),
  vol. 23, no. 2, pp. 287-291, Feb. 2016
  (paper, code, bib).
• P.-K. Jao, Y.-H. Yang, and B. Wohlberg,
  "Informed monaural source separation of music based on convolutional sparse coding,"
  IEEE International Conference on Acoustics, Speech and Signal Processing 2015 (ICASSP’15).
  (paper, code, project)
• T.-S. Chan, T.-C. Yeh, Z.-C. Fan, H.-W. Chen, L. Su, Y.-H. Yang, and J.-S. Jang,
  "Vocal activity informed singing voice separation with the IKALA dataset,"
  IEEE International Conference on Acoustics, Speech and Signal Processing 2015 (ICASSP’15).
  (paper, data)
• Y.-H. Yang,
  "Low-rank representation of both singing voice and music accompaniment via learned dictionaries,"
  in Proc. Int. Society for Music Information Retrieval 2013 (ISMIR'13), pp. 427-432.
  (paper, code, detailed result)
• Y.-H. Yang,
  "On sparse and low-rank matrix decomposition for singing voice separation,"
  in Proc. ACM Multimedia 2012 (MM'12), short paper, pp. 757-760.
  (paper)

Music Transcription (back to top)

• Ching-Yu Chiu, Meinard Müller, Matthew E. P. Davies, Alvin Wen-Yu Su, and Yi-Hsuan Yang,
  "Local periodicity-based beat tracking for expressive classical piano music,"
  IEEE/ACM Transactions on Audio, Speech, and Language Processing (TASLP), vol. 31, pp. 2824-2835, July 2023.
  (paper, code)
• Ching-Yu Chiu, Meinard Müller, Matthew E. P. Davies, Alvin Wen-Yu Su, and Yi-Hsuan Yang,
  "An analysis method for metric-level switching in beat tracking,"
  IEEE Signal Processing Letters (SPL), vol. 29, pp. 2153-2157, Oct. 2022.
  (paper, code)
• Yu-Hua Chen, Wen-Yi Hsiao, Tsu-Kuang Hsieh, Jyh-Shing Roger Jang, and Yi-Hsuan Yang,
  "Towards automatic transcription of polyphonic electric guitar music: A new dataset and a multi-loss transformer model,"
  in Proc. IEEE International Conference on Acoustics, Speech and Signal Processing 2022 (ICASSP’22).
  (paper, demo, data)
• Ching-Yu Chiu, Alvin Wen-Yu Su, and Yi-Hsuan Yang,
  "Drum-aware ensemble architecture for improved joint musical beat and downbeat tracking,"
  IEEE Signal Processing Letters (SPL), vol. 28, pp. 1100-1104, May 2021.
  (paper, code)
• Ching-Yu Chiu, Joann Ching, Wen-Yi Hsiao, Yu-Hua Chen, Alvin Wen-Yu Su, Yi-Hsuan Yang,
  "Source separation-based data augmentation for improved joint beat and downbeat tracking,"
  in Proc. European Signal Processing Conference 2021 (EUSIPCO’21).
  (paper, code)
• Tsung-Han Hsieh, Li Su, and Yi-Hsuan Yang,
  "A streamlined encoder/decoder architecture for melody extraction,"
  in Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing 2019 (ICASSP’19).
  (paper, code)
• Yun-Ning Hung, Yi-An Chen and Yi-Hsuan Yang,
  "Multitask learning for frame-level instrument recognition,"
  in Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing 2019 (ICASSP’19).
  (paper, code)
• Yun-Ning Hung, Yi-An Chen and Yi-Hsuan Yang,
  "Learning disentangled representations for timber and pitch in music audio,"
  in ArXiv e-prints, abs/1811.03271, November 2018.
  (paper)
• Yun-Ning Hung and Yi-Hsuan Yang,
  "Frame-level instrument recognition by timbre and pitch,"
  in Proc. Int. Society for Music Information Retrieval Conf. 2018 (ISMIR'18), pp. 135-142
  (paper, arxiv, demo, code, bib)
• Lufei Gao, Li Su, Yi-Hsuan Yang, and Tan Lee
  "Polyphonic piano note transcription with non-negative matrix factorization of differential spectrogram,"
  in Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing 2017 (ICASSP’17).
  (paper)
• M.-H. Yang, L. Su and Y.-H. Yang,
  "Highlighting root notes in chord recognition using cepstral features and multi-task learning,"
  in Proc. Asia Pacific Signal and Information Processing Association Annual Summit and Conf. 2016 (APSIPA ASC’16).
  (paper)
• L. Su, T.-Y. Chuang and Y.-H. Yang,
  "Exploiting frequency, periodicity and harmonicity using advanced time-frequency concentration techniques for multipitch estimation of choir and symphony,"
  in Proc. Int. Society for Music Information Retrieval Conf. 2016 (ISMIR’16).
  (paper, data)
• C.-Y. Liang, L. Su, H.-M. Lin and Y.-H. Yang,
  "Musical offset detection of pitched instruments: the case of violin,"
  in Proc. Int. Society for Music Information Retrieval Conf. 2015 (ISMIR'15), pp. 281-287.
  (paper, data)
• L. Su and Y.-H. Yang,
  "Escaping from the Abyss of Manual Annotation: New Methodology of Building Polyphonic Datasets for Automatic Music Transcription,"
  in Proc. Int. Symp. Computer Music Multidisciplinary Research 2015 (CMMR’15).
  (paper)
• C.-Y. Liang, L. Su and Y.-H. Yang,
  "Musical onset detection using constrained linear reconstruction,"
  IEEE Signal Processing Letters (SPL),
  vol. 22, no. 11, pp. 2142-2146, Nov. 2015
  (paper, code, bib).
• L. Su and Y.-H. Yang,
  "Combining spectral and temporal representations for multipitch estimation of polyphonic music,"
  IEEE/ACM Transactions on Audio, Speech, and Language Processing (TASLP),
  vol. 23, no. 10, pp. 1600-612, Oct. 2015
  (paper, bib).
• L. Su and Y.-H. Yang,
  "Power-scaled spectral flux and peak-valley group-delay methods for robust musical onset detection,"
  in Proc. Sound and Music Computing Conf. 2014 (SMC’14).
  (paper)
• L. Su, L.-F. Yu, Y.-H. Yang, and H.-Y. Lai,
  "Resolving octave ambiguities: A cross-dataset Investigation,"
  in Proc. Sound and Music Computing Conf. 2014 (SMC’14).
  (paper, data)
• C.-T. Lee, Y.-H. Yang and H.-H. Chen,
  "Multipitch estimation of piano music by exemplar-based sparse representation,"
  IEEE Transactions on Multimedia (TMM),
  vol. 14, no. 3, pp. 608-618, Jun. 2012.
  (paper, bib) [project page]
• C.-D. Lee, Y.-H. Yang, and H.-H. Chen,
  "Automatic transcription of piano music by sparse representation of magnitude spectra,"
  in Proc. IEEE Int. Conf. Multimedia and Expo. 2011 (ICME'11).
  (paper) [project page]

• H.-T. Cheng, Y.-H. Yang, Y.-C. Lin, I.-B. Liao, and H.-H. Chen,
  "Automatic chord recognition for music classification and retrieval,"
  in Proc. IEEE Int. Conf. Multimedia and Expo. 2008 (ICME'08), Hannover, Germany, pp. 1505-1508.
  (paper)

Structure Analysis (back to top)

• Taejun Kim, Yi-Hsuan Yang, and Juhan Nam,
  "Joint estimation of fader and equalizer gains of DJ mixers using convex optimization," 
  in Proc. Int. Conf. Digital Audio Effects 2022 (DAFx’22).
  (paper)
• Taejun Kim, Yi-Hsuan Yang, and Juhan Nam,
  "Reverse-engineering the transition regions of real-world DJ mixes using sub-band analysis with convex optimization," 
  in Proc. International Conference on New Interface for Musical Expression 2021 (NIME’21).
  (paper)
• Taejun Kim, Minsuk Choi, Evan Sacks, Yi-Hsuan Yang, and Juhan Nam,
  "A computational analysis of real-world DJ mixes using mix-to-track subsequence alignment,"
  in Proc. Int. Society for Music Information Retrieval Conf. 2020 (ISMIR'20).
  (paper, code)
• Yu-Siang Huang, Szu-Yu Chou and Yi-Hsuan Yang,
  "Pop music highlighter: Marking the emotion keypoints,"
  Transactions of the International Society for Music Information Retrieval (TISMIR),
  vol.1, no. 1, pp. 68-78, 2018.
  (paper, code, arxiv)
• Yu-Siang Huang, Szu-Yu Chou and Yi-Hsuan Yang,
  "Generating music medleys via playing music puzzle games,"
  in Proc. AAAI Conf. Artificial Intelligence (AAAI’18), 2018
  (paper, demo, code, bib)
• Yu-Siang Huang, Szu-Yu Chou and Yi-Hsuan Yang,
  "DJnet: A Dream for Making An Automatic DJ,"
  ISMIR demo paper (non-peer reviewed two-page extended abstract) 2017 (ISMIR'17-LBD).
  (paper)
• Yu-Siang Huang, Szu-Yu Chou and Yi-Hsuan Yang,
  "Music thumbnailing via neural attention modeling of music emotion,"
  in Proc. Asia Pacific Signal and Information Processing Association Annual Summit and Conf. 2017 (APSIPA ASC’17), pp. 347-350.
  (paper, demo)
• M.-Y. Su, Y.-H. Yang, Y.-C. Lin, and H.-H. Chen,
  "An integrated approach to music boundary detection,"
  in Proc. Int. Society for Music Information Retrieval 2009 (ISMIR'09), pp. 705-710.
  (paper, poster)
• H.-T. Cheng, Y.-H. Yang, Y.-C. Lin, and H.-H. Chen,
  "Multimodal structure segmentation and analysis of music using audio and textual information,"
  in Proc. IEEE Int. Symp. Circuits and Systems 2009 (ISCAS'09), Taipei, Taiwan, pp. 1677-1680.
  (paper) [project page, include dataset]

Performance/expressivity (back to top)

• Ting-Wei Su, Yuan-Ping Chen, Li Su, and Yi-Hsuan Yang,
  "TENT: Technique-embedded note tracking for real-world guitar solo recordings,"
  Transactions of the International Society for Music Information Retrieval (TISMIR),
  vol. 2, no. 1, pp. 15-28, 2019.
  (paper)
• Chi-Ching Shih, Pei-Ching Li, Yi-Ju Lin, Alvin W. Y. Su, Li Su and Yi-Hsuan Yang,
  "Analysis and synthesis of the violin playing styles of Heifetz and Oistrakh,"
  in Proc. Int. Conf. Digital Audio Effects 2017 (DAFx'17),
  accepted for publication
  (paper)
• C.-H. Yang, P.-C. Li, A. W. Y. Su, L. Su, and Y.-H. Yang,
  "Automatic violin synthesis using expressive musical term features,"
  in Proc. Int. Conf. Digital Audio Effects 2016 (DAFx'16),
  (paper)
• Yin-Jyun Luo, Li Su, Yi-Hsuan Yang and Tai-Shih Chi,
  "Detection of common mistakes in novice violin playing,"
  in Proc. Int. Society for Music Information Retrieval Conf. 2015 (ISMIR'15), pp. 316-322.
  (paper)
• Yuan-Ping Chen, Li Su and Yi-Hsuan Yang,
  "Electric guitar playing technique detection in real-world recording based on F0 sequence pattern recognition,"
  in Proc. Int. Society for Music Information Retrieval Conf. 2015 (ISMIR'15), pp. 708-714.
  (paper, data)
• Pei-Ching Li, Li rSu, Yi-Hsuan Yang and Alvin W. Y. Su,
  "Analysis of expressive musical terms in violin using score-informed and expression-based audio features,"
  in Proc. Int. Society for Music Information Retrieval Conf. 2015 (ISMIR'15), pp. 809-815.
  (paper, data)
• Li Su, Li-Fan Yu arnd Yi-Hsuan Yang,
  "Sparse cepstral and phase codes for guitar playing technique classification,"
  in Proc. Int. Society for Music Information Retrieval Conf. 2014 (ISMIR'14), pp. 9-14.
  (paper, data)

Recommendation (back to top)

• Szu-Yu Chou, Jyh-Shing Roger Jang, and Yi-Hsuan Yang,
  "Fast tensor factorization for large-scale context-aware recommendation from implicit feedback,"
  IEEE Transactions on Big Data (TBD),
  vol. 6, no. 1, pp. 201-208, Mar. 2020.
  (paper, bib)
• Chih-Ming Chen, Chuan-Ju Wang, Ming-Feng Tsai and Yi-Hsuan Yang,
  "Collaborative similarity embedding for recommender systems,"
  in Proc. the Web Conference 2019 (WWW’19), short paper (acceptance rate 20%),
  (paper, arxiv)
• Chia-An Yu, Ching-Lun Tai, Tak-Shing Chan and Yi-Hsuan Yang,
  "Modeling multi-way relations with hypergraph embedding,"
  in Proc. ACM International Conference on Information and Knowledge Management 2018 (CIKM’18),
  accepted.
  (paper, code, bib)
• Asmita Poddar, Eva Zangerle, and Yi-Hsuan Yang,
  "#nowplaying-RS: A new benchmark dataset for building context-aware music recommender systems,"
  in Proc. Sound and Music Computing Conf. 2018 (SMC’18),
  accepted.
  (paper, code, data)
• Chih-Ming Chen, Yi-Hsuan Yang, Yi-An Chen, Ming-Feng Tsai,
  "Vertex-context sampling for weighted network embedding,"
  in ArXiv e-prints, abs/1711.00227, Nov 2017.
  (paper)
• Chia-An Yu, Tak-Shing Chan and Yi-Hsuan Yang,
  "Low-rank matrix completion over finite Abelian group algebras for context-aware recommendation,"
  in Proc. ACM International Conference on Information and Knowledge Management 2017 (CIKM’17),
  accepted.
  (paper, code, bib)
• S.-Y. Chou, L.-C. Yang, Y.-H. Yang, and J.-S. Jang,
  "Conditional preference nets for user and item cold start problems in music recommendation,"
  in Proc. IEEE Int. Conf. Multimedia and Expo. 2017 (ICME’17),
  accepted.
  (paper, bib)
• S.-Y. Chou, Y.-H. Yang, J.-S. Jang and Y.-C. Lin,
  "Addressing cold start for next-song recommendation,"
  in Proc. ACM Recommender Systems (RecSys’16), 4-page short paper for oral presentation, pp. 115-118,
  (paper, code, bib)
• C.-M. Chen, M.-F. Tsai, Y.-C. Lin and Y.-H. Yang,
  "Query-based music recommendations via preference embedding,"
  in Proc. ACM Recommender Systems (RecSys’16), 4-page short paper for oral presentation, pp. 79-82.
  (paper, bib)
• C.-M. Chen, P.-C. Chien, M.-F. Tsai, Y.-H. Yang and Y.-C. Lin,
  "Exploiting latent social listening representations for music recommendations,"
  in Proc. ACM Recommender Systems (RecSys’15), 2-page poster paper.
  (paper)
• S.-Y. Chou, Y.-H. Yang, and Y.-C. Lin,
  "Evaluating music recommendation in a real-world setting: On data splitting and evaluation metrics,"
  in Proc. IEEE Int. Conf. Multimedia and Expo. (ICME’15). (Best Paper Award)
  (paper)
• C.-M. Chen, H.-P. Chen, M.-F. Tsai, and Y.-H. Yang,
  "Leverage item popularity and recommendation quality via cost-sensitive factorization machines,"
  in Proc. IEEE Int. Conf. Data Mining (ICDM’14), Ph.D. forum paper.
  (paper)
• C.-M. Chen, M.-F. Tsai, J.-Y. Liu, and Y.-H. Yang,
  "Using emotional context from article for contextual music recommendation."
  in Proc. ACM Int. Conf. Multimedia 2013 (MM'13), short paper (acceptance rate 30%).
  (paper, demo)
• C.-M. Chen, M.-F. Tsai, J.-Y. Liu, and Y.-H. Yang,
  "Music recommendation based on multiple contextual similarity information."
  in Proc. IEEE/WIC/ACM Int. Conf. Web Intelligence 2013 (WI'13).
  (paper)
• Y.-C. Teng, Y.-S. Kuo, and Y.-H. Yang,
  "A large in-situ dataset for context-aware music recommendation on smartphones,"
  in Proc. IEEE Int. Conf. Multimedia and Expo. 2013 (ICME'13), short paper.
  (paper)
• J.-Y. Liu and Y.-H. Yang,
  "Inferring personal traits from music listening history,"
  in Int. Workshop on Music Information Retrieval with User-Centered and Multimodal Strategies (MIRUM'12), in conjunction with ACM Multimedia (MM), pp. 31-36.
  (paper, bib)
• Y.-H. Yang and H.-H. Chen,
  "iMR: Interactive music recommendation via active interactive genetic algorithm,"
  in Proc. Int. Workshop on Computer Music and Audio Technology 2009 (WOCMAT'09), Taipei, Taiwan.
  (paper)

Music and Video (back to top)

• Yu-Chih Tsai, Tse-Yu Pan, Ting-Yang Kao, Yi-Hsuan Yang, and Min-Chun Hu,
  "EMVGAN: Emotion-aware music-video common representation learning via generative adversarial networks,"
  in Proc. Int. Joint Workshop on Multimedia Artworks Analysis and Attractiveness Computing in Multimedia, in conjunction with ACM ICMR, 2022.
  (paper)
• Jen-Yu Liu, Yi-Hsuan Yang, and Shyh-Kang Jeng,
  "Weakly-supervised visual instrument-playing action detection in videos,"
  IEEE Transactions on Multimedia (TMM),
  vol. 21, no. 4, pp. 887-901, Apr. 2019.
  (paper, bib, arxiv)
• Jen-Chun Lin, Wen-Li Wei, Tyng-Luh Liu, Yi-Hsuan Yang, Hsin-Min Wang, Hsiao-Rong Tyan, and Hong-Yuan Mark Liao,
  "Coherent deep-net fusion to classify shots in concert videos,"
  IEEE Transactions on Multimedia (TMM),
  vol. 20, no. 11, pp. 3123-3136, Nov. 2018.
  (paper, demo, bib)
• Wen-Li Wei, Jen-Chun Lin, Tyng-Luh Liu, Yi-Hsuan Yang, Hsin-Min Wang, Hsiao-Rong Tyan, and Hong-Yuan Mark Liao,
  "SeetheVoice: Learning from music to visual storytelling of shots,"
  in Proc. IEEE Int. Conf. Multimedia and Expo. 2018 (ICME’18).
  (paper, demo)
• Wen-Li Wei, Jen-Chun Lin, Tyng-Luh Liu, Yi-Hsuan Yang, Hsin-Min Wang, Hsiao-Rong Tyan, and Hong-Yuan Mark Liao,
  "Deep-net fusion to classify shots in concert videos,"
  in Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing 2017 (ICASSP’17).
  (paper, demo)
• C.-H. Yeh, Y.-H. Yang, M.-H. Chang, and H.-Y. M. Liao,
  "Music driven human motion manipulation for characters in a video,"
  in Proc. IEEE Int. Symp. Multimedia (ISM’14).
  (paper)
• Ju-Chiang Wang, Ming-Chi Yan, Yi-Hsuan Yang and Hsin-Min Wang,
  "Automatic set list identification and song segmentation of full-length concert videos,"
  in Proc. Int. Society for Music Information Retrieval Conf. 2014 (ISMIR'14), pp. 239-244.
  (paper)
• J.-C. Wang, Y.-H. Yang, I.-H. Jhuo, Y.-Y. Lin, and H.-M. Wang,
  "The Acousticvisual Emotion Gaussians model for automatic generation of music video,"
  in Proc. ACM Multimedia 2012 (MM'12), Grand Challenge solution paper (first prize), pp. 1379-1380.
  (paper, demo)
• K.-S. Lin, A. Lee, Y.-H. Yang, C.-D. Lee, and H.-H. Chen,
  "Automatic highlights extraction for drama video using music emotion and human face features,"
  in Proc. IEEE Int. Workshop on Multimedia Signal Processing 2011 (MMSP'11).
  (paper).

Retrieval (back to top)

• P.-I. Chen, J.-Y. Liu, and Y.-H. Yang,
  "Personal Factors in Music Preference and Similarity: User Study on the Role of Personality Traits,"
  in Proc. Int. Symp. Computer Music Multidisciplinary Research 2015 (CMMR’15),
  (paper).
• Y.-H. Yang, W.-H. Hsu, and H.-H. Chen,
  "Online reranking via ordinal informative concepts for context fusion in concept detection and video search,"
  IEEE Transactions on Circuits and Systems for Video Technology (TCSVT),
  vol. 19, no. 12, pp. 1880-1890, Dec. 2009.
  (paper, bib)
• Y.-H. Yang, P.-T. Wu, C.-W. Lee, K.-H. Lin, W.-H. Hsu, and H.-H. Chen,
  "ContextSeer: Context search and recommendation at query time for shared consumer photos,"
  in Proc. ACM Multimedia 2008 (MM'08) (full paper, content track, accept rate=21%), pp. 199-208.
  (paper, slides) [project page, include dataset]
• P.-T. Wu, Y.-H. Yang, K.-T. Chen, W.-H. Hsu, T.-H. Li, and C.-J. Lee,
  "Keyword-based corncept search on consumer photos by web-based kernel function,"
  in Proc. ACM Multimedia 2008 (MM'08) (poster, content track), pp. 651-654.
  (paper)
• Y.-H. Yang and W.-H. Hsu,
  "Video search reranking via online ordinal reranking,"
  in Proc. IEEE Int. Conf. Multimedia and Expo. 2008 (ICME'08), Hannover, Germany.
  (paper)

Editorial (back to top)

• Meinard Müller, Emilia Gómez, and Yi-Hsuan Yang,
  "Computational methods for melody and voice processing in music recordings,"
  Report from Dagstuhl Seminar 19052,
  2019.
  (paper)
• M. Schedl, Y.-H. Yang, and P. Herrera,
  "Introduction to intelligent music systems and applications,"
  ACM Transactions on Intelligent Systems and Technology (TIST),
  vol. 8, no. 2, article 17, Dec. 2016.
  (paper, bib)
• Hsin-Min Wang, Yi-Hsuan Yang, and Jin Ha Lee,
  International Society for Music Information Retrieval Conference,
  Proceedings, ISMIR, Taipei, Taiwan, 2014.
  (link)

Others (back to top)

• Zhe-Cheng Fan, Tak-Shing T. Chan, Yi-Hsuan Yang, and Jyh-Shing R. Jang,
  "Backpropagation with N-D vector-valued neurons using arbitrary bilinear products,"
  IEEE Transactions on Neural Networks and Learning Systems (TNNLS),
  vol. 31, no. 7, pp. 2638-2652, 2020.
  (paper)
• Zhe-Cheng Fan, Tak-Shing Chan, Yi-Hsuan Yang and Jyh-Shing Jang,
  "Deep cyclic group networks,"
  in Proc. Int. Joint Conf. Neural Networks 2019 (IJCNN’19),
  (paper).
• Z.-C. Fan, T.-S. T. Chan, Y.-H. Yang, and J.-S. R. Jang,
  "Music signal processing using vector product neural networks,"
  International Workshop on Deep Learning for Music 2017 (DLM’17).
  (paper)
• P.-K. Jao, P.-I. Chen, and Y.-H. Yang,
  "Disk Jockey in Brain - A Prototype for Volume Control of Tracked Instrument during Playback,"
  in Proc. Int. Works. Brain-Computer Music Interfacing 2015 (BCMI’15),
  (paper).
• Y.-F. Su, Y.-H. Yang, M.-T. Lu, and H.-H. Chen,
  "Smooth control of adaptive media playout for video streaming,"
  IEEE Transactions on Multimedia (TMM),
  vol. 11, no. 7, pp. 1331-1339, Nov. 2009.
  (paper, bib)

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