Speech and Audio Signal Processing: Processing and Perception of Speech and Music
Speech and Audio Signal Processing: Processing and Perception of Speech and Music
Fuzzy Logic
Data compression with fuzzy relational equations
Fuzzy Sets and Systems - Information processing
MICAI'05 Proceedings of the 4th Mexican international conference on Advances in Artificial Intelligence
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Fuzzy Systems
Fuzzy vector quantization algorithms and their application in image compression
IEEE Transactions on Image Processing
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Data compression is always advisable when it comes to handling and processing information quickly and efficiently. There are two main problems that need to be solved when it comes to handling data; store information in smaller spaces and processes it in the shortest possible time. When it comes to infant cry analysis (ICA), there is always the need to construct large sound repositories from crying babies. Samples that have to be analyzed and be used to train and test pattern recognition algorithms; making this a time consuming task when working with uncompressed feature vectors. In this work, we show a simple, but efficient, method that uses Fuzzy Relational Product (FRP) to compresses the information inside a feature vector, building with this a compressed matrix that will help us recognize two kinds of pathologies in infants; Asphyxia and Deafness. We describe the sound analysis, which consists on the extraction of Mel Frequency Cepstral Coefficients that generate vectors which will later be compressed by using FRP. There is also a description of the infant cry database used in this work, along with the training and testing of a Time Delay Neural Network with the compressed features, which shows a performance of 96.44% with our proposed feature vector compression.