Automatic Discrimination in Audio Documents

In this paper, we present a content-based classification approach for audio indexing. The classification is based on low level audio features such as temporal sound, energy, fundamental frequency, zero crossing rate, auto correlation curve, and based on transformations such as Short Time Fourier Transform (STFT). The audio classification in classes such as music, noise, silence, and speech is an efficient indexing method, because it permits efficient searches, by limiting the searches in the suitable classes.