👉 Mel Computing is an innovative field that focuses on developing computational models and algorithms inspired by the human auditory system, particularly Mel-frequency cepstral coefficients (MFCCs), to process and analyze audio signals. This approach, rooted in psychoacoustics, aims to mimic how humans perceive sound, making it particularly effective for tasks such as speech recognition, music information retrieval, and audio classification. By transforming audio signals into the mel-scale, a perceptually meaningful representation of frequency, Mel Computing enables more efficient and accurate processing of audio data, bridging the gap between human auditory perception and machine learning. This interdisciplinary field combines insights from psychology, signal processing, and machine learning to create robust and efficient audio analysis systems.
