Open Access

ARTICLE

Speech-Music-Noise Discrimination in Sound Indexing of Multimedia Documents

Lamia Bouafif¹, Noureddine Ellouze²

1 National Institute of Biomedical Studies of Tunis, 1092, Tunis, Tunisia
2 Image and Signal Processing Laboratory, ENIT BP 37, University of Tunis El Manar, 1064, Tunisia
The authors can be reached at: b2lamia@yahoo.fr.

Sound & Vibration 2018, 52(6), 2-10. https://doi.org/10.32604/sv.2018.02410

Abstract

Sound indexing and segmentation of digital documents especially in the internet and digital libraries are very useful to simplify and to accelerate the multimedia document retrieval. We can imagine that we can extract multimedia files not only by keywords but also by speech semantic contents. The main difficulty of this operation is the parameterization and modelling of the sound track and the discrimination of the speech, music and noise segments. In this paper, we will present a Speech/Music/Noise indexing interface designed for audio discrimination in multimedia documents. The program uses a statistical method based on ANN and HMM classifiers. After pre-emphasis and segmentation, the audio segments are analysed by the cepstral acoustic analysis method. The developed system was evaluated on a database constituted of music songs with Arabic speech segments under several noisy environments.

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Keywords

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