Research On Content-based Audio Retrieval Technology And System Achievement

With the exponential growth in the production creation of multimedia data recent year, there is an increasing need for video semantic analysis. Audio, as a significant part of multimedia data, provides important cues to human perception when humans are browsing and understanding video/audio contents.This paper analyses the situation and disadvantage of audio retrieval, some basic conceptions and retrieval method are introduced. And discusses the feature exaction and expression of WAV form audio signal, proved the audio layered segmentation algorithm to template-based audio segmentation algorithm, By making use of the Hidden Markov Model's beer stochastic sequence and superiority independent of concrete threshold, the veracity of segmentation and recognize is enhanced a lot; and analyzed the HMM based classification model to different audio example feature. This paper design a content-based audio retrieval original system, with good expansibility. Do a effective and efficiency retrieval. And finally look into the distance to the hot spot and the systematic developing trend on CBIA.