Computer Music Research Group - IME/USP Report for SBCM 2019
Resumo
The following report presents some of the ongoing projects that are taking place in the group’s laboratory. One of the noteable characteristics of this group is the extensive research spectrum, the plurality of research areas that are being studied by it’s members, such as Music Information Retrieval, Signal Processing and New Interfaces for Musical Expression.
Palavras-chave:
Digital Sound Processing, Music Information Retrieval, Sensors and Multimodal Signal Processing
Referências
meinard müller. fundamentals of music processing: audio, analysis, algorithms, applications. 2015.
Justin Salamon, Joan Serrà, and Emilia Gómez. Tonal representations for music retrieval: from version identification to query-by-humming. Int. J. of Multimedia Info. Retrieval, special issue on Hybrid Music Info. Retrieval, 2(1):45–58, Mar. 2013.
Ernesto López, Martı́n Rocamora, and Gonzalo Sosa. Búsqueda de música por tarareo, 2004.
Bartłomiej Stasiak. Follow that tune – adaptive approach to dtw-based query-by-humming system. ARCHIVES OF ACOUSTICS, 39(4):467–476, 2014.
Alexios Kotsifakos, Panagiotis Papapetrou, Jaakko Hollmen, Dimitrios Gunopulos, Vassilis Athitsos, and George Kollios. Hum-a-song: A subsequence matching with gapsrange-tolerances query-by-humming system. 5(10), 2012.
Judith C Brown. Calculation of a constant q spectral transform. The Journal of the Acoustical Society of America, 89(1):425–434, 1991.
Alexey Lukin and Jeremy Todd. Adaptive time-frequency resolution for analysis and processing of audio. In Audio Engineering Society Convention 120. Audio Engineering Society, 2006.
Florent Jaillet and Bruno Torrésani. Time-frequency jigsaw puzzle: Adaptive multiwindow and multilayered gabor expansions. International Journal of Wavelets, Multiresolution and Information Processing, 5(02):293–315, 2007.
Rodney G Vaughan, Neil L Scott, and D Rod White. The theory of bandpass sampling. IEEE Transactions on signal processing, 39(9):1973–1984, 1991.
Otso Lähdeoja. Active acoustic instruments for electronic chamber music. 2016.
Edgar Joseph Berdahl. Applications of feedback control to musical instrument design. Stanford University, 2010.
Andrew McPherson and Victor Zappi. An environment for submillisecond-latency audio and sensor processing on beaglebone black. In Audio Engineering Society Convention 138. Audio Engineering Society, 2015.
Francesco Ricci, Lior Rokach, Bracha Shapira, and Paul B. Kantor. Recommender Systems Handbook. SpringerVerlag, Berlin, Heidelberg, 1st edition, 2010.
Rodrigo Borges and Marcelo Queiroz. Automatic music recommendation based on acoustic content and implicit listening feedback. Revista Música Hodie, 18(1):31 – 43, jun. 2018.
A. L. Berenzweig, D. P. W. Ellis, and S. Lawrence. Using voice segments to improve artist classification of music. In 22nd Int. Conf.: Virtual, Synthetic, and Entertainment Audio. Audio Engineering Society, 2002.
Yipeng Li and DeLiang Wang. Separation of singing voice from music accompaniment for monaural recordings. Technical report, Ohio State University Columbus United States, 2005.
J. Salamon and E. Gómez. Melody extraction from polyphonic music signals using pitch contour characteristics. IEEE Transactions on Audio, Speech, and Language Processing, 20(6):1759–1770, Aug. 2012.
Shayenne Moura and Marcelo Queiroz. Melody and accompaniment separation using enhanced binary masks. In Proceedings of the 16th Brazilian Symposium on Computer Music, pages 164 – 165, São Paulo, 2017. 17th Brazilian Symposium on Computer Music - SBCM 2019
Kyungyun Lee, Keunwoo Choi, and Juhan Nam. Revisiting singing voice detection: a quantitative review and the future outlook. In 19th Int. Soc. for Music Info. Retrieval Conf., Paris, France, 2018.
Shayenne Moura. Singing voice detection using vggish embeddings. 19th International Society for Music Information Retrieval Conference, Paris, France, 2018.
Justin Salamon, Joan Serrà, and Emilia Gómez. Tonal representations for music retrieval: from version identification to query-by-humming. Int. J. of Multimedia Info. Retrieval, special issue on Hybrid Music Info. Retrieval, 2(1):45–58, Mar. 2013.
Ernesto López, Martı́n Rocamora, and Gonzalo Sosa. Búsqueda de música por tarareo, 2004.
Bartłomiej Stasiak. Follow that tune – adaptive approach to dtw-based query-by-humming system. ARCHIVES OF ACOUSTICS, 39(4):467–476, 2014.
Alexios Kotsifakos, Panagiotis Papapetrou, Jaakko Hollmen, Dimitrios Gunopulos, Vassilis Athitsos, and George Kollios. Hum-a-song: A subsequence matching with gapsrange-tolerances query-by-humming system. 5(10), 2012.
Judith C Brown. Calculation of a constant q spectral transform. The Journal of the Acoustical Society of America, 89(1):425–434, 1991.
Alexey Lukin and Jeremy Todd. Adaptive time-frequency resolution for analysis and processing of audio. In Audio Engineering Society Convention 120. Audio Engineering Society, 2006.
Florent Jaillet and Bruno Torrésani. Time-frequency jigsaw puzzle: Adaptive multiwindow and multilayered gabor expansions. International Journal of Wavelets, Multiresolution and Information Processing, 5(02):293–315, 2007.
Rodney G Vaughan, Neil L Scott, and D Rod White. The theory of bandpass sampling. IEEE Transactions on signal processing, 39(9):1973–1984, 1991.
Otso Lähdeoja. Active acoustic instruments for electronic chamber music. 2016.
Edgar Joseph Berdahl. Applications of feedback control to musical instrument design. Stanford University, 2010.
Andrew McPherson and Victor Zappi. An environment for submillisecond-latency audio and sensor processing on beaglebone black. In Audio Engineering Society Convention 138. Audio Engineering Society, 2015.
Francesco Ricci, Lior Rokach, Bracha Shapira, and Paul B. Kantor. Recommender Systems Handbook. SpringerVerlag, Berlin, Heidelberg, 1st edition, 2010.
Rodrigo Borges and Marcelo Queiroz. Automatic music recommendation based on acoustic content and implicit listening feedback. Revista Música Hodie, 18(1):31 – 43, jun. 2018.
A. L. Berenzweig, D. P. W. Ellis, and S. Lawrence. Using voice segments to improve artist classification of music. In 22nd Int. Conf.: Virtual, Synthetic, and Entertainment Audio. Audio Engineering Society, 2002.
Yipeng Li and DeLiang Wang. Separation of singing voice from music accompaniment for monaural recordings. Technical report, Ohio State University Columbus United States, 2005.
J. Salamon and E. Gómez. Melody extraction from polyphonic music signals using pitch contour characteristics. IEEE Transactions on Audio, Speech, and Language Processing, 20(6):1759–1770, Aug. 2012.
Shayenne Moura and Marcelo Queiroz. Melody and accompaniment separation using enhanced binary masks. In Proceedings of the 16th Brazilian Symposium on Computer Music, pages 164 – 165, São Paulo, 2017. 17th Brazilian Symposium on Computer Music - SBCM 2019
Kyungyun Lee, Keunwoo Choi, and Juhan Nam. Revisiting singing voice detection: a quantitative review and the future outlook. In 19th Int. Soc. for Music Info. Retrieval Conf., Paris, France, 2018.
Shayenne Moura. Singing voice detection using vggish embeddings. 19th International Society for Music Information Retrieval Conference, Paris, France, 2018.
Publicado
25/09/2019
Como Citar
GORODSCY, Fábio; FEULO, Guilherme; FIGUEIREDO, Nicolas; ITABORAÍ, Paulo Vitor; BODO, Roberto; BORGES, Rodrigo; MOURA, Shayenne.
Computer Music Research Group - IME/USP Report for SBCM 2019. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO MUSICAL (SBCM), 17. , 2019, São João del-Rei.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2019
.
p. 189-191.
DOI: https://doi.org/10.5753/sbcm.2019.10443.
