Research And Implementation Of Content-based Audio Retrieval Technology

How to analyze . store and retrieve the huge amount of data efficiently and effectively, especially forthose multimedia data is an imperative problem. Because of the nonstructural character, the development of audio retrieval is restricted hugely. Comparing with image and video retrieval, audio retrieval study is behindhand. Content-based audio retrieval has been the studied hotspot of multimedia retrieval. This paper focuses on the key techniques of content-based audio retrieval, developed mainly in the following aspect:1. This paper analyzes audio feature extraction and expression. Audio retrieval completes through multiple features combination. This paper studies the audio perceptive features, such as loudness, brightness and pitch etc, and the audio physical feature, such as zero-crossing rate, linear prediction coefficient and Mel cepstrum coefficient etc. Different features combination can be applied in different audio retrieval.2. This paper study audio segmentation and recognize, and proved the audio layered segmentation algorithm to template-based audio segmentation algorithm, making use of the Hidden Markov Model's better stochastic sequence and superiority independent of concrete threshold, the veracity of segmentation and recognize is enhanced a lot Because compressed audio format MPEG has been the mainstream of multimedia encoding, this paper studies the feature extraction onMP3 directly and audio segmentation on MPEG.3. This paper study content-based audio retrieval. Studying from query by audio example, aiming at different audio example expression, mis paper studies the query by audio example algorithm based on Hidden Markov Model classification template and fuzzy clustering centroid respectively Aiming at music(song)'s unique character, mis paper studies muskXsong) retrieval by Humming, and does some performance test, the algorithm has high veracity.