Audio Environment Recognition using Zero Crossing Features and MPEG-7 Descriptors
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Problem statement: This study investigated zero crossing features and selected MPEG-7 audio descriptors for environment sound recognition applications such as audio forensics. Approach: The study implemented several experiments focusing on the problems of environment recognition from audio particularly for forensic applications. Results: It was investigated the effect of the temporal zero crossing feature as well as selected MPEG-7 audio low level descriptors on environment sound recognition. The performance was evaluated against a varying number of training sounds and samples per training file. Conclusion/Recommendations: Experimental results showed that higher recognition accuracy is achieved by increasing the number of training files and by decreasing the number of samples per training file. This study presented an audio environment recognition using zero crossing features and MPEG-7 Descriptors.
Copyright: © 2021 Saleh Al-Zhrani and Mubarak AlQahtani. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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- Audio forensics
- zero crossing