Semantic context detection based on hierarchical audio models

Wen Huang Cheng, Wei Ta Chu, Ja Ling Wu

研究成果: Conference contribution

71 引文 斯高帕斯(Scopus)

摘要

Semantic context detection is one of the key techniques to facilitate efficient multimedia retrieval. Semantic context is a scene that completely represents a meaningful information segment to human beings. In this paper, we propose a novel hierarchical approach that models the statistical characteristics of several audio events, over a time series, to accomplish semantic context detection. The approach consists of two stages: audio event and semantic context detections. HMMs are used to model basic audio events, and event detection is performed in the first stage. Then semantic context detection is achieved based on Gaussian mixture models, which model the correlations among several audio events temporally. With this framework, we bridge the gaps between low-level features and the semantic contexts that last in a time series. The experimental evaluations indicate that the approach is effective in detecting high-level semantics.

原文English
主出版物標題Proceedings of the 5th ACM SIGMM International Workshop on Multimedia Information Retrieval, MIR 2003
發行者Association for Computing Machinery, Inc
頁面109-115
頁數7
ISBN(電子)1581137788, 9781581137781
DOIs
出版狀態Published - 2003 十一月 7
事件5th ACM SIGMM International Workshop on Multimedia Information Retrieval, MIR 2003 - Berkeley, United States
持續時間: 2003 十一月 7 → …

出版系列

名字Proceedings of the 5th ACM SIGMM International Workshop on Multimedia Information Retrieval, MIR 2003

Conference

Conference5th ACM SIGMM International Workshop on Multimedia Information Retrieval, MIR 2003
國家/地區United States
城市Berkeley
期間03-11-07 → …

All Science Journal Classification (ASJC) codes

  • 媒體技術
  • 軟體
  • 資訊系統
  • 電腦科學應用
  • 訊號處理

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