VOIP compressed-domain automatic speaker recognition based on probabilistic stochastic histogram
| Autor: | Wang Bingxi, Tang Hui, Yan Honggang, Qu Dan |
|---|---|
| Rok vydání: | 2008 |
| Předmět: |
Stochastic process
Computer science business.industry Feature vector Speech recognition ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Probabilistic logic Vector quantization Histogram matching Pattern recognition Data_CODINGANDINFORMATIONTHEORY Mixture model Speaker recognition ComputingMethodologies_PATTERNRECOGNITION Computer Science::Sound Computer Science::Computer Vision and Pattern Recognition Histogram Artificial intelligence business |
| Zdroj: | 2008 9th International Conference on Signal Processing. |
| DOI: | 10.1109/icosp.2008.4697225 |
| Popis: | Compressed-domain automatic speaker recognition is based on the analysis of the compressed parameters of speech coders. This paper presents compressed-domain speaker recognition approach based on the Probabilistic Stochastic Histogram algorithm. We propose a framework based on Vector Quantization Probabilistic Stochastic Histogram(VQPSH) algorithm and perform speaker recognition on the feature vector which is directly extracted from G.729, G.723.1 6.3k, G723.1 5.3k compressed bit stream. We also propose a speaker recognition algorithm based on Gaussian Mixture Model Probabilistic Stochastic Histogram (GMMPSH). The experimental results show the Probabilistic Stochastic Histogram is superior to classical GMM using the same feature vector. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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