Biblio

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Laurier, C., & Herrera P. (2009).  Automatic Detection of Emotion in Music: Interaction with Emotionally Sensitive Machines. (Vallverdu, J., Casacuberta, D., Ed.).Handbook of Research on Synthetic Emotions and Sociable Robotics: New Applications in Affective Computing and Artificial Intelligence. 9-32.
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Gouyon, F., Widmer G., & Serra X. (2005).  Acoustic Cues to Beat Induction A Machine Learning Perspective. 10th Rhythm Perception and Production Workshop. 24(2), 177-188. Abstract
Gong, R. (2018).  Automatic Assessment of Singing Voice Pronunciation: A Case Study with Jingju Music. Department of Information and Communications Technologies. xxxii + 235. Abstract
Gong, R., Pons J., & Serra X. (2017).  Audio to Score Matching by Combining Phonetic and Duration Information. The 18th International Society for Music Information Retrieval Conference. Abstract
Gómez, E., Bonada J., & Salamon J. (2012).  Automatic Transcription of Flamenco Singing from Monophonic and Polyphonic Music Recordings. III Interdisciplinary Conference on Flamenco Research (INFLA) and II International Workshop of Folk Music Analysis (FMA). Abstract
Gómez, P., Pikrakis A., Mora J., Díaz-Báñez J. M., Gómez E., Escobar Borrego F., et al. (2012).  Automatic Detection of Melodic Patterns in Flamenco Singing by Analyzing Polyphonic Music Recordings. III Interdisciplinary Conference on Flamenco Research (INFLA) and II International Workshop of Folk Music Analysis (FMA). Abstract
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