Academic literature on the topic 'Tamil Music'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Tamil Music.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Journal articles on the topic "Tamil Music"
Narayanan, Jayakrishnan. "The Linguistic Reluctance of Karnatik Music: From Tamil to Madras Tamil." Journal of Exclusion Studies 9, no. 2 (2019): 194. http://dx.doi.org/10.5958/2231-4555.2019.00016.0.
Full textHughes, Stephen Putnam. "Music in the Age of Mechanical Reproduction: Drama, Gramophone, and the Beginnings of Tamil Cinema." Journal of Asian Studies 66, no. 1 (February 2007): 3–34. http://dx.doi.org/10.1017/s0021911807000034.
Full textHornabrook, Jasmine. "Tamil folk music as Dalit liberation theology." Ethnomusicology Forum 25, no. 2 (April 19, 2016): 241–43. http://dx.doi.org/10.1080/17411912.2016.1170621.
Full textP, Divyaroobasharma. "The Raise of Tamilisai by Thevara Moover." International Research Journal of Tamil 3, S-2 (April 30, 2021): 98–101. http://dx.doi.org/10.34256/irjt21s219.
Full textBhalke, Daulappa Guranna, Betsy Rajesh, and Dattatraya Shankar Bormane. "Automatic Genre Classification Using Fractional Fourier Transform Based Mel Frequency Cepstral Coefficient and Timbral Features." Archives of Acoustics 42, no. 2 (June 27, 2017): 213–22. http://dx.doi.org/10.1515/aoa-2017-0024.
Full textIm, Bo kyung Blenda. "Book Review: Tamil Folk Music as Dalit Liberation Theology." International Bulletin of Mission Research 39, no. 2 (April 2015): 105–6. http://dx.doi.org/10.1177/239693931503900223.
Full textAravinthon, Suganya. "A Historical Perspective of Mangalavattiyam." International Research Journal of Tamil 3, no. 2 (March 3, 2021): 1–10. http://dx.doi.org/10.34256/irjt2121.
Full textP, Divyarupasarma. "Sitrilakiyangalil Kavadi Sindhu." International Research Journal of Tamil 3, S-1 (June 22, 2021): 234–37. http://dx.doi.org/10.34256/irjt21s137.
Full textRajesh, Betsy, and D. G. Bhalke. "Automatic genre classification of Indian Tamil and western music using fractional MFCC." International Journal of Speech Technology 19, no. 3 (June 18, 2016): 551–63. http://dx.doi.org/10.1007/s10772-016-9347-3.
Full textMeddegoda, Chinthaka Prageeth. "Hindustani Classical Music in Sri Lanka: A Dominating Minority Music or an Imposed Musical Ideology?" ASIAN-EUROPEAN MUSIC RESEARCH JOURNAL 6 (December 4, 2020): 41–50. http://dx.doi.org/10.30819/aemr.6-3.
Full textDissertations / Theses on the topic "Tamil Music"
Hornabrook, Jasmine. "'Becoming one again' : music and transnationalism in London's Sri Lankan Tamil diaspora." Thesis, Goldsmiths College (University of London), 2016. http://research.gold.ac.uk/18533/.
Full textLai, JinXing. "The Hindu Fire Walking Festival in Singapore: Ritual and Music of the Tamil Diaspora." Ohio University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1397250646.
Full textCelma, Herrada Òscar. "Music recommendation and discovery in the long tail." Doctoral thesis, Universitat Pompeu Fabra, 2009. http://hdl.handle.net/10803/7557.
Full textEls algorismes de recomanació de música actuals intenten predir amb precisió el que els usuaris demanen escoltar. Tanmateix, molt sovint aquests algoritmes tendeixen a recomanar artistes famosos, o coneguts d'avantmà per l'usuari. Això fa que disminueixi l'eficàcia i utilitat de les recomanacions, ja que aquests algorismes es centren bàsicament en millorar la precisió de les recomanacions. És a dir, tracten de fer prediccions exactes sobre el que un usuari pugui escoltar o comprar, independentment de quant útils siguin les recomanacions generades. En aquesta tesi destaquem la importància que l'usuari valori les recomanacions rebudes. Per aquesta raó modelem la corba de popularitat dels artistes, per tal de poder recomanar música interessant i desconeguda per l'usuari.
Les principals contribucions d'aquesta tesi són: (i) un nou enfocament basat en l'anàlisi de xarxes complexes i la popularitat dels productes, aplicada als sistemes de recomanació, (ii) una avaluació centrada en l'usuari, que mesura la importància i la desconeixença de les recomanacions, i (iii) dos prototips que implementen la idees derivades de la tasca teòrica. Els resultats obtinguts tenen una clara implicació per aquells sistemes de recomanació que ajuden a l'usuari a explorar i descobrir continguts que els pugui agradar.
Actualmente, el consumo de música está sesgada hacia algunos artistas muy populares. Por ejemplo, en el año 2007 sólo el 1% de todas las canciones en formato digital representaron el 80% de las ventas. De igual modo, únicamente 1.000 álbumes representaron el 50% de todas las ventas, y el 80% de todos los álbumes vendidos se compraron menos de 100 veces. Existe, pues, una necesidad de ayudar a los usuarios a filtrar, descubrir, personalizar y recomendar música a partir de la enorme cantidad de contenido musical existente. Los algoritmos de recomendación musical existentes intentan predecir con precisión lo que la gente quiere escuchar. Sin embargo, muy a menudo estos algoritmos tienden a recomendar o bien artistas famosos, o bien artistas ya conocidos de antemano por el usuario.Esto disminuye la eficacia y la utilidad de las recomendaciones, ya que estos algoritmos se centran en mejorar la precisión de las recomendaciones. Con lo cuál, tratan de predecir lo que un usuario pudiera escuchar o comprar, independientemente de lo útiles que sean las recomendaciones generadas.
En este sentido, la tesis destaca la importancia de que el usuario valore las recomendaciones propuestas. Para ello, modelamos la curva de popularidad de los artistas con el fin de recomendar música interesante y, a la vez, desconocida para el usuario.Las principales contribuciones de esta tesis son: (i) un nuevo enfoque basado en el análisis de redes complejas y la popularidad de los productos, aplicada a los sistemas de recomendación,(ii) una evaluación centrada en el usuario que mide la calidad y la novedad de las recomendaciones, y (iii) dos prototipos que implementan las ideas derivadas de la labor teórica. Los resultados obtenidos tienen importantes implicaciones para los sistemas de recomendación que ayudan al usuario a explorar y descubrir contenidos que le puedan gustar.
Music consumption is biased towards a few popular artists. For instance, in 2007 only 1% of all digital tracks accounted for 80% of all sales. Similarly, 1,000 albums accounted for 50% of all album sales, and 80% of all albums sold were purchased less than 100 times. There is a need to assist people to filter, discover, personalise and recommend from the huge amount of music content available along the Long Tail.Current music recommendation algorithms try to accurately predict what people demand to listen to. However, quite often these algorithms tend to recommend popular -or well-known to the user- music, decreasing the effectiveness of the recommendations. These approaches focus on improving the accuracy of the recommendations. That is, try to make accurate predictions about what a user could listen to, or buy next, independently of how useful to the user could be the provided recommendations.
In this Thesis we stress the importance of the user's perceived quality of the recommendations. We model the Long Tail curve of artist popularity to predict -potentially- interesting and unknown music, hidden in the tail of the popularity curve. Effective recommendation systems should promote novel and relevant material (non-obvious recommendations), taken primarily from the tail of a popularity distribution.
The main contributions of this Thesis are: (i) a novel network-based approach for recommender systems, based on the analysis of the item (or user) similarity graph, and the popularity of the items, (ii) a user-centric evaluation that measures the user's relevance and novelty of the recommendations, and (iii) two prototype systems that implement the ideas derived from the theoretical work. Our findings have significant implications for recommender systems that assist users to explore the Long Tail, digging for content they might like.
Sjöberg, Mikael. ""Hur känd kan jag bli på fem veckor?" : En studie om distribution av musik via Internet." Thesis, Södertörn University College, School of Communication, Media and it, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:sh:diva-3219.
Full textInternet and the digital channels for distribution have meant big changes for the musicindustry. The physical record that has been symbolising this market for a long time is slowlybeing replaced by digital based music. The technical progress during the last ten years has ledto a democratization of music production. The amateur musicians of today can produce highquality music on their laptops and later distribute it via free music sites. MySpace andYouTube are two of the biggest sites for this free distribution and is therefore my main choiseof study.
The purpose of this essay was to find out how and if these changes have made a difference formusicians without a record deal to reach an audience by themselves. In order to find this out Iconducted three qualitative personal interviews with both established and amateur musiciansworking in the music business.
To find out how many listeners a amateur musician can generate on their own within a shortamount of time I made a quantitative study during five weeks where I posed as an musicianstarting from scrach with an aim to become famous. During these five weeks I got my songplayed 164 times and got to collaborate with a podcast show from England.
My hypothesis has been that the future role of the record company will be reduced andpossibly disappear. The theories in this essay argues that this might indeed be the case whenmusicians have accsess to a world o free marketing.
Internet och de digitala distributionskanalerna har inneburit stora förändringar för musikindustrin. Den fysiska skivan som länge har symboliserat denna marknad försvinner bytssakta men säkert ut mot digitalt baserad musik. De tekniska framgångarna under de senastetio åren har lett till en demokratisering av musik produktion. Amatörmusiker kan idagproducera musik med hög kvalitet på en laptop och sprida den gratis med hjälp av sajter förgratis musik. MySpace och YouTube representerar två av de största kanalerna för dennaspridning av gratis musik och jag har därför valt att fokusera min undersökning till dessa tvåsajter.
Syftet med denna uppsats var att at reda på hur och om denna förändring inomdistributionsmöjligheterna har förändrat förutsättningarna för musiker utan skivkontrakt attsprida sin musik och hitta en publik på egen hand. För att studera detta utförde jag trekvalitativa intervjuer med etablerade musiker och amatörmusiker inom musikbranschen.
För att ta reda på hur många lyssnare en amatörmusiker kan generera på egen hand under enkortare tid utförde jag en kvantitativ studie under loppet av fem veckor. I denna undersökningsatte jag mig själv in i rollen som amatörmusiker med en målsättning att bli känd. Underdessa fem veckor fick jag min låt spelad 164 gånger och fick även medverka på en podcastfrån England.
Min hypotes var att skivbolagen kommer att spela en mindre roll i framtidens musikscen ochkanske rent utav att försvinna. Teorierna som behandlas i denna uppsats talar för detta. I envärld där musiker har tillång till gratis marknadsföring och spridning av musik, vem behöverdå skivbolagen?
Kuylenstierna, Adam. "Underground in the Cloud : En kvalitativ studie om den digitala musikplattformen Soundcloud." Thesis, Stockholms universitet, Institutionen för journalistik, medier och kommunikation (JMK), 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-58932.
Full text"Music recommendation and discovery in the long tail." Universitat Pompeu Fabra, 2009. http://www.tesisenxarxa.net/TDX-0612109-190038/.
Full textHuang, Yi-ching, and 黃益青. "The Study of Network Recommendation Method in Long Tail Market''s Two Sides Application: Take Taiwan''s Digital Music Industry as an Example." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/84242134743483930509.
Full text逢甲大學
企業管理所
96
Web2.0 is the contour and new game rule of latter network world. Long Tail is the network marketing criterion and new economics of the culture creative industry in Web2.0 world. The music industry changed rapidly in the last decade, and the product sales changed from physical CD disks to digital music. All industry emerged from the new patterns in essential and operational. The proposes of the research are to explore (1) the fit of latter Taiwan''s digital music industry application in Web2.0 and Long Tail; (2) the recommendation effect of the network recommendation method in that; (3) the future developing tendency in digital music industry. Through the exploration of research questions with perspectives of bibliographical conferring, this research divides consumers'' preferences of the top mass market and the rear niche market into audiences of pop music and niche music. The types of latter digital music divide into three types: P2P Files Exchange, Streaming and Charge for Downloading. Network recommendation method divide equally emphasized basis of media and information in marketing effect into two dimensions: the message''s media sources and the recommendation message''s delivery. Through in-depth interview, this research has discovered that (1) P2P Files Exchange is the most prevalent channel of consumers'' illegal downloading music; (2) Streaming has developed to the popular legal digital music; (3) it''s hard to survive due to Charge for Downloading is too expensive. Furthermore, the consumers of preferring niche music have better accepted recommendation effect to (1) the message''s media sources of higher autonomous content; (2) the recommendation message''s delivery of higher individual controlling content.
Books on the topic "Tamil Music"
Tamil folk music as Dalit liberation theology. Bloomington: Indiana University Press, 2012.
Find full textIyengar, R. Rangaramanuja. Carnatic music pallavi tradition =: Karnāṭaka saṅkīta pallavi sampiratayam : pala rāka tāḷaṅkaḷil sāhittiya neraval, jāti vin̲yāsam, an̲ulōma pratilōmam, svara pstāram ivar̲r̲ai viḷakkum 25 pallavikaḷ. Mumbai: Vipanchi Cultural Trust, 1997.
Find full textKuppuswami, T. V. Situating sound and rhythm: Music of Tamil Nadu. New Delhi: Gyan Pub. House, 1999.
Find full textKuppuswami, T. V. Carnātic music and the Tamils. Delhi: Kalinga Publications, 1992.
Find full textSundararaman. RagaChintamani: A guide to Carnatic ragas through Tamil film music. Chennai: Pichhamal Chintamani, 2005.
Find full textBhagyalekshmy, S. Carnatic music compositions: An index. Trivandrum: CBH Publications, 1994.
Find full textKulēntiran̲, Ñān̲ā. Teyvat Tamil̲icai. Tañcāvūr: Kiruṣṇi Patippakam, 1994.
Find full textBook chapters on the topic "Tamil Music"
Celma, Òscar. "The Long Tail in Recommender Systems." In Music Recommendation and Discovery, 87–107. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13287-2_4.
Full textCraw, Susan, Ben Horsburgh, and Stewart Massie. "Music Recommendation: Audio Neighbourhoods to Discover Music in the Long Tail." In Case-Based Reasoning Research and Development, 73–87. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24586-7_6.
Full textNayak, Suraj Kumar, Utkarsh Srivastava, D. N. Tibarewala, Goutam Thakur, Biswajit Mohapatra, and Kunal Pal. "Effect of Odia and Tamil Music on the ANS and the Conduction Pathway of Heart of Odia Volunteers." In Pattern and Data Analysis in Healthcare Settings, 240–63. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-0536-5.ch012.
Full textAhmed, Omar. "Representing Terrorism." In Studying Indian Cinema, 183–200. Liverpool University Press, 2015. http://dx.doi.org/10.3828/liverpool/9781906733681.003.0011.
Full textWeidman, Amanda. "The Remarkable Career of L. R. Eswari." In Vamping the Stage. University of Hawai'i Press, 2017. http://dx.doi.org/10.21313/hawaii/9780824869861.003.0008.
Full textMiller, Malcolm. "Ancient Symbols, Modern Meanings The Use of the Shofar in Twentieth- and Twenty-First-Century Music." In Qol Tamid, 165–220. Claremont Press, 2018. http://dx.doi.org/10.2307/j.ctvbcd1px.12.
Full text"A Standard of Socialist Cinema: The Clear River Tamir (Tungalag Tamir, 1970–1973)." In Mongolian Film Music, 93–112. Routledge, 2016. http://dx.doi.org/10.4324/9781315596044-12.
Full textVedral, Vlatko. "Place Your Bets: In It to Win It." In Decoding Reality. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198815433.003.0012.
Full text"Glossary Bailian Jiao White Lotus teachings baimiao paying homage at the temples ban band caijie street procession cha, ban small cymbals chi hui hold a feast for all the households chuige songs for winds chuigu shou drumers and wind players dangzi gong in frame daqu large pieces dizi transverse flute with kazoo membrane fang dengke releasing the lanterns fangshe or shishi pardon and distribution of food fang hedeng releasing the river lanterns gongche traditional notation gu large barrel drum guanshi, zan guan helper guanzi double-reed pipe guyueban, chuida ban wind-and-percussion band huahui assembly of performing troupes hui association huishou association head nanyue the southern music nao, bo large cymbals pai prelude paizi percussion pieces, cf. the melodic qupai qu pieces qupai labelled melodies shang miao going to the temple shan hui charitable associations she society she hui altar assembly shen body sheng free-reed mouth organ sheng-guan yue type of wind-and-percussion music shenghui outstanding association shifu masters tao suites wei tail xiangshou incense head xiaoqu small pieces xueshi learning the [ritual] business xuyuan make vows to the gods." In Tradition & Change Performance, 48. Routledge, 2012. http://dx.doi.org/10.4324/9780203985656-10.
Full textConference papers on the topic "Tamil Music"
Supriya, P., R. Jayabarathi, C. Jeyanth, Yogeshwar Ba, Adith Sarvesh, and Mohamed Shurfudeen. "Preliminary Investigation for Tamil cine music deployment for mood music recommender system." In 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS). IEEE, 2020. http://dx.doi.org/10.1109/icaccs48705.2020.9074249.
Full textFerraro, Andres. "Music cold-start and long-tail recommendation." In RecSys '19: Thirteenth ACM Conference on Recommender Systems. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3298689.3347052.
Full textDomingues, Marcos Aurélio, Fabien Gouyon, Alípio Mário Jorge, José Paulo Leal, João Vinagre, Luís Lemos, and Mohamed Sordo. "Combining usage and content in an online music recommendation system for music in the long-tail." In the 21st international conference companion. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2187980.2188224.
Full textDomingues, Marcos Aurelio, and Solange Oliveira Rezende. "The Impact of Context-Aware Recommender Systems on Music in the Long Tail." In 2013 Brazilian Conference on Intelligent Systems (BRACIS). IEEE, 2013. http://dx.doi.org/10.1109/bracis.2013.28.
Full text