@InProceedings{gulati2016ragaRecognition_ismir,
  Title                    = {Time-delayed melody surfaces for r{\={a}}ga recognition},
  Author                   = {Gulati, Sankalp and Serr{\`a}, Joan and Ganguli, Kaustuv K. and {\c S}ent{\"u}rk, Sertan and Serra, Xavier},
  Booktitle                = {Proceedings of 17th International Society for Music Information Retrieval Conference (ISMIR 2016)},
  Year                     = {2016},

  Address                  = {New York, NY, USA},
  Pages                    = {751--757},

  Abstract                 = {R{\={a}}ga is the melodic framework of Indian art music. It is a core concept used in composition, performance, organization, and pedagogy. Automatic r{\={a}}ga recognition is thus a fundamental information retrieval task in Indian art music. In this paper, we propose the time-delayed melody surface (TDMS), a novel feature based on delay coordinates that captures the melodic outline of a r{\={a}}ga. A TDMS describes both the tonal and the temporal characteristics of a melody, using only an estimation of the predominant pitch. Considering a simple k-nearest neighbor classifier, TDMSs outperform the state-of-the-art for r{\={a}}ga recognition by a large margin. We obtain 98\% accuracy on a Hindustani music dataset of 300 recordings and 30 r{\={a}}gas, and 87\% accuracy on a Carnatic music dataset of 480 recordings and 40 r{\={a}}gas. TDMSs are simple to implement, fast to compute, and have a musically meaningful interpretation. Since the concepts and formulation behind the TDMS are generic and widely applicable, we envision its usage in other music traditions beyond Indian art music.},
  File                     = {:publications/gulati2016ragarecognition_ismir.pdf:PDF},
  Url                      = {http://sertansenturk.com/uploads/publications/gulati2016ragarecognition_ismir.pdf}
}