Noise reduction based on Nearest Neighbor Estimation for audio feature extraction

With the rapid expansion of modern multimedia data, a number of audio fingerprinting algorithms have been proposed. Audio fingerprint is a compact unique content-based digital signature of an audio signal, which can be used to identify unknown audio clips. Due to the interference of different kinds of noise, audio fingerprinting is still a challenging task. In this paper, Nearest Neighbor Estimation (NNE) is used to reduce the interference of the noise. Firstly, audio feature points are extracted from audio clips. Then NNE is used to reduce the impact of noise on the feature points. Experimental results show that NNE reduces the influence of noise effectively in white noise environment.