Abstract
Audio interactive applications have eased our lives in numerous ways encompassing speech recognition to song identification. Such applications have helped the common people in using Information Technology by providing them a passage for skipping the complicated user interactivity procedures. Audio based search applications have become very popular nowadays especially for searching songs. A system which can distinguish between speech and songs can help to boost the performance of such applications by minimizing the search space and at the same time decide the method of recognition based on the type of audio. It can also help in music-speech separation from audio for karaoke development. In this paper, a system to segregate songs and speech has been proposed using Line Spectral Pair based features. The system has been tested on a database of 19374 clips and a highest accuracy of 99.88% has been obtained with Ensemble Learning based classification.
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Mukherjee, H., Phadikar, S., Roy, K. (2018). Segregation of Speech and Songs - A Precursor to Audio Interactive Applications. In: Mandal, J., Sinha, D. (eds) Social Transformation – Digital Way. CSI 2018. Communications in Computer and Information Science, vol 836. Springer, Singapore. https://doi.org/10.1007/978-981-13-1343-1_5
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DOI: https://doi.org/10.1007/978-981-13-1343-1_5
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