Mel Frequency Cepstral Coefficient

Mel-frequency cepstral coefficients (MFCCs) are a widely used feature representation for audio signals, primarily aimed at capturing perceptually relevant information for tasks like speech recognition and classification. Current research focuses on optimizing MFCC parameter settings for improved performance in various applications, including disease diagnosis from voice and music genre classification, and exploring alternative or complementary feature extraction methods, such as those based on raw waveforms or spectrograms processed by convolutional neural networks. The effectiveness of MFCCs, and the ongoing exploration of their limitations and improvements, significantly impacts the accuracy and efficiency of numerous audio processing applications across diverse fields.