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This paper proposes a semantic music discovery system based on a tag-level factor graph (TFG) model with utilization of tag probability and content similarity in a unified fashion. The content similarities are calculated based on the extracted pitch features while tag probabilities are obtained from our previous auto-tagging system. The TFG model consists of a set of node and edge feature functions,...
This paper proposes a music auto-tagging system based on probabilistic annotation of semantically meaningful tags with variable feature sets. The perception-related long-term features are extracted. The original features are selected by a combination algorithm of ReliefF and principle component analysis (PCA) to form a variable unique feature subset for each tag. The Gaussian mixture models (GMMs)...
This paper presents a preliminary analysis of differences of formants among Shanghai, Guangzhou, Chongqing and Xiamen dialectal Putonghua (PTH) in China. An improved formant model based on the linear prediction (LP) feature analysis and a two-dimensional(2D) hidden Markov model (HMM) of formants is employed for estimation of the formant frequencies of vowels and diphthongs. The experiments show Guangzhou...
At present, object-extraction is one of the key problems of the data-procession to the aerial LIDAR dataset. The aim of this paper is to research the methods to classify and extract the object-points from the cloud points obtained by the aerial LIDAR system. In this paper, based on the different feature of elevation and intensity of different objects, the laser-points of buildings, vegetation and...
In our previous work, a speech/music classifier is proposed on the basis of the feature subset selection (FSS) tool and oblique decision tree induced by the algorithm OC1. In this paper, we endeavor to improve it by state transfer (ST) strategy whose aim is to refine the classification results, according to the fact that adjacent segments in one audio file have strong relevance to each other. The...
Although technologies of both low-level and high-level descriptors for music information retrieval (MIR) are advancing, there are some essential deficiencies while utilizing them separately. In this paper we propose a model where the low-level and high-level descriptors collaborate to support semantics-based MIR. The ontology of ldquomusic scenerdquo domain is constructed as a demonstration, and a...
The existing voice activity detectors (VAD) always depend on specific audio codecs and give the degraded performance in the existence of music signals. This paper presents a sound activity detection method independent of audio codecs. An entropy feature set with adaptive noise estimation update is proposed to improve the performance of the entropy in detecting both speech and music. Afterwards, a...
In this paper, we established a new general semiautomatic building rooftop extraction method applied for high resolution satellite imagery. Based on investigation of the current existed methods for building extraction and its feature extraction, a general framework of building rooftop extraction is proposed. To extract the precise building roof boundary, an seeded region growth segmentation or localized...
This paper presents a novel graph search schema for right-angle building extraction from high resolution aerial and satellite image subsets which contain a building. As the schema is a edge-driven and bottom-up approach, emphasis is put on elimination of spurious and insignificant low-level image features. In real-world, most buildings are comprised of several sequential corners. We classify the corners...
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