Abstract
Melody is the soul of the Indian classical music for raga identification. This paper evaluates different algorithms proposed for raga recognition for effectiveness and computational cost. As per the analysis done, the pitch class distribution and N-gram approaches found out to be more effective. It was revealed that none of the research focused on the facet of minimum duration sample required for identification. The main aim of the experiments is to identify the least duration sample required for identification of raga. Least duration will lead to less computational cost and time. Dataset used is voiced audio samples of monophonic music with duration of audio samples ranging from 30 to 180 s from the beginning of raga rendition. Pitch extraction for melodic data is done using auto correlation method in tool praat. Findings revealed that different ragas require varied duration for accurate identification. Potential directions to improve the raga identification performance with less possible duration are proposed.
Similar content being viewed by others
References
Ramesh VM (2008) Exploring data analysis in music using tool praat. In: IEEE emerging trends engineering technologies, pp. 508–509. https://doi.org/10.1109/ICETET.2008.83
Schmidt-Jones C (2011) Indian classical music: tuning and ragas. Connexions, OpenStax-CNX module: m12459, pp 1–7
Ross JC, Vinutha TP, Rao P (2012) Detecting melodic motifs from audio for hindustani classical music. In: ISMIR, pp. 193–198
Rao S, Rao P (2014) An overview of Hindustani music in the context of computational musicology. J New Music Res 43(1):24–33
Ganguli KK, Gulati S, Serra X, Rao P (2016) Data-driven exploration of melodic structure in Hindustani music. In: International Society for Music Information Retrieval, https://www.upf.edu/handle.net/10230/33062, pp. 605–611
Gulati S, Serrà Julià J, Ganguli KK, Sentürk S, Serra X (2016) Time-delayed melody surfaces for Rāga recognition. In: International Society for Music Information (ISMIR), https://www.upf.edu/handle/10230/33117, pp. 751–757
Ganguli KK, Lele A, Pinjani S, Rao P, Srinivasamurthy A, Gulati S (2017) Melodic shape stylization for robust and efficient motif detection in hindustani vocal music. In: Communications (NCC), 2017 twenty-third national conference on, pp. 1–6, IEEE, 2017
Sarkar R, Naskar SK, Saha SK (2017) Raga identification from Hindustani classical music signal using compositional properties. Comput Visual Sci. https://doi.org/10.1007/s00791-017-0282-x
Padmasundari G, Murthy HA (2017) Raga identification using locality sensitive hashing. IEEE National Conference on Communications (NCC), pp. 1–6. https://doi.org/10.1109/NCC.2017.8077058
Anitha R, Gunavathi K (2017) NCM-based raga classification using musical features. Int J Fuzzy Syst 19(5):1603–1616
Ross, JC, Mishra A, Ganguli KK, Bhattacharyya P, Rao P (2017) Identifying raga similarity through embeddings learned from composition’s notation In: Proceedings of the 18th international society for music information retrieval conference, ISMIR, pp. 515–522
Banerjee S (2017) A survey of prospects and problems in hindustani classical raga identification using machine learning techniques. In: Proceedings of the first international conference on intelligent computing and communication, pp. 467–475. Springer, Singapore, 2017
Gulati S et al (2014) Automatic tonic identification in Indian art music: approaches and evaluation. J New Music Res 43(1):53–71
Sridhar R, Geetha TV (2009) Raga identification of carnatic music for music information retrieval. Int J Recent Trends Eng 1(1):571–574
Zhang YG, Zhang CS (2005) Separation of voice and music by harmonic structure stability analysis. In: IEEE international conference in multimedia and expo, ICME
Pandey G, Mishra C, Ipe P (2003) Tansen: a system for automatic raga identification. In: 1st Indian international conference on artificial intelligence, Hyderabad
Sinith MS, Rajeev K (2006) Hidden Markov model based recognition of musical pattern in sound Indian classical music. In: Proceedings of IEEE international conference on signal and image processing
Rao V, Rao P (2010) Vocal melody extraction in the presence of pitched accompaniment in polyphonic music. IEEE Trans Audio Speech Lang Process 18(8):2145–2154
Chordia P, Rae A (2007) Raag recognition using pitch-class and pitch-class dyad distributions. In: Proceedings of ISMIR
Apel W (1950) Harvard dictionary of music, Cambridge. Harvard University Press, Massachusetts
Shreyas Belle RJPR (2009) Raga identification by using swara intonation. J ITC Sangeet Res Acad 23
http://www.fon.hum.uva.nl/praat/ Accessed 15 Jun 2018
Makarand V, Parag K (2018) Unified algorithm for melodic music similarity and retrieval in query by humming. In: Intelligent computing and information and communication. Advances in intelligent systems and computing, vol. 673. Springer, Singapore, pp 373–381. https://doi.org/10.1007/978-981-10-7245-1_37
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Velankar, M., Deshpande, A. & Kulkarni, P. Melodic pattern recognition in Indian classical music for raga identification. Int. j. inf. tecnol. 13, 251–258 (2021). https://doi.org/10.1007/s41870-018-0245-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s41870-018-0245-6