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Mining movie archives for song sequences

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Abstract

Music and songs are integral parts of Bollywood movies. Every movie of two to three hours, contains three to ten songs, each song is 3–10 min long. Music lovers like to listen music and songs of a movie, however it is time consuming and error prone to search manually all the songs in a movie. Moreover, the task becomes much harder when songs are to be extracted from a huge archived movies’ database containing hundreds of movies. This paper presents an approach to automatically extract music and songs from archived musical movies. We used song grammar to construct Markov Chain Model that differentiates song scenes from dialogue and action scenes in a movie. We tested our system on Bollywood, Hollywood, Pakistani, Bengali, and Tamil movies. A total of 20 movies from different industries were selected for the experiments. On Bollywood movies, we achieved 97.22% recall in song extraction, whereas the recall on Hollywood musical movies is 80%. The test result on Pakistani, Tamil and Bengali movies is 87.09%.

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Authors and Affiliations

  1. Computer Science and Information Management, Asian Institute of Technology, Bangkok, Thailand

    Sher Muhammad Doudpota

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  1. Sher Muhammad Doudpota
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Correspondence to Sher Muhammad Doudpota.

Additional information

The preliminary idea of this paper was published in the Proceedings of International Conference on Database and Data Mining (ICDDM), July 2010, Manila, Philippines.

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Doudpota, S.M. Mining movie archives for song sequences. Multimed Tools Appl 69, 359–382 (2014). https://doi.org/10.1007/s11042-012-1021-4

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