Fuzzy Clustering Approach Using Data Fusion Theory and Its Application to Automatic Isolated Word Recognition
نویسنده
چکیده
In this paper, utilization of clustering algorithms for data fusion in decision level is proposed. The results of automatic isolated word recognition, which are derived from speech spectrograph and Linear Predictive Coding (LPC) analysis, are combined with each other by using fuzzy clustering algorithms, especially fuzzy k-means and fuzzy vector quantization. Experimental results show that the proposed algorithms have better performance, compared to classical clustering. Key Word Data Fusion Theory, K-Means Clustering, Fuzzy K-Means, Fuzzy Vector Quantization هديـكچ هشوخ ياهمتـيروگلا درـبراك ،هـلاقم نـيا رد يارب يدنب بيكرت ميمصت حطس رد تاعلاطا هيارا يريگ يـم دوـش . فلتخم ياهشور زا هك ،ازجم تاملك راكدوخ صيخشت جياتـن ) ياهوگلا و راتفگ فارگورتكپسا دننام راتـفگ يـنامز ( يـم تـسدب هشوخ ياهمتيروگلا زا هدافتسا اب ، دنـيآ يزاف يدنب صوصخب ، k-means و يزاف يم بيكرت رگيدكي اب يزاف يرادرب هدنـنك يدنـچ دنوش . جياتن هدايپ يم ناشن يزاس هدش هيارا ياهمتيروگلا دهد هشوخ كيسلاك ياهشور اب هسياقم رد يرتهب يياراك دراد يدنب .
منابع مشابه
Fuzzy Clustering Approach Using Data Fusion Theory and its Application To Automatic Isolated Word Recognition
In this paper, utilization of clustering algorithms for data fusion in decision level is proposed. The results of automatic isolated word recognition, which are derived from speech spectrograph and Linear Predictive Coding (LPC) analysis, are combined with each other by using fuzzy clustering algorithms, especially fuzzy k-means and fuzzy vector quantization. Experimental results show that the...
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