Report of the ISMIS 2011 Contest: Music Information Retrieval

Automatic music genre classification based on musical instrument track separation

“…This aspect may have a very positive impact on the effectiveness of classification experiment. Still, as reported in the literature, for low level-feature-based approach and multi-class recognition, the effectiveness of music genre classification is in the range of 60-80% (Bergstra et al 2006;Tzanetakis et al 2002;Holzapfel and Stylianou 2008;Kostek et al 2011) with some exceptions (see e.g. Ntalampiras (2013)).…”

“…Feature vectors (FVs) for music genre classification are usually based on low-level descriptors from the MPEG-7 standard (Lindsay and Herre 2001;Hyoung-Gook et al 2005), Mel-Frequency Cepstral Coefficients (MFCCs) (Tzanetakis et al 2002) or finally, dedicated parameters suggested by researchers (Kostek 1999;Kostek et al 2011;Liu et al 2007;Nayak and Bhutani 2011;Salamon et al 2012;Silla et al 2007). Table 1 presents a list of parameters contained in the Synat database .…”

“…Table 1 presents a list of parameters contained in the Synat database . Most parameters are based on the MPEG-7 standard, and the remaining ones are the MFCC descriptors and time-related dedicated parameters (Kostek et al 2011). Since definitions of these parameters are well-known or easily found in the literature sources, they are not to be recalled here.…”

“…The authors and their collaborators performed several studies devoted to AMGC (Kostek 2013;Kostek et al 2011;Kostek et al 2014;Plewa and Kostek 2015;Rosner et al 2014;Rosner and Kostek 2015), in which decision algorithms, such as: kNNs (k Nearest Neighbors), SVM by Sequential Minimal Optimization (SMO) algorithm, Rough Sets and Bayesian Networks were used. Recently, a paper was published by one of the authors and her Ph.D. student (Hoffmann and Kostek 2015), which presents a novel approach to the Virtual Bass Synthesis (VBS) applied to mobile devices, called Smart VBS (SVBS).…”

Music Information Retrieval – Soft Computing Versus Statistics

“…They are venues devoted to MIR only (e.g. ISMIR, MIREX) [18] [20][24] [34] in which state-of-the-art MIR methods and achievements are critically evaluated, also sessions, workshops, discussion panels dedicated to this domain occur within artificial intelligence, audio, multimedia and other symposia and conferences [14] [16][17] [23]. On the other hand, there exist many music recommendation services, commercial and non-commercial that are based on social networking rather than on MIR-related methods [31][38] [39[40][41].…”