Description: 这是一个很好的支持向量机工具箱，它可用于模式识别，图像识别，文字识别，语音识别和手写体识别等领域。-This is a very good support vector machine toolbox, it can be used for pattern recognition, image recognition, text recognition, speech recognition and handwriting recognition and other fields. Platform: |
Size: 4445184 |
Author:李全林 |
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Description: 支持向量机,是一种用于分类的新技术.目前在语音识别中用的比较少.-Support Vector Machine is a new technology for the classification. Currently used in speech recognition is relatively small. Platform: |
Size: 327680 |
Author:weidanfang |
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Description: SVMstruct is a Support Vector Machine (SVM) algorithm for predicting multivariate or structured outputs. It performs supervised learning by approximating a mapping
h: X --> Y
using labeled training examples (x1,y1), ..., (xn,yn). Unlike regular SVMs, however, which consider only univariate predictions like in classification and regression, SVMstruct can predict complex objects y like trees, sequences, or sets. Examples of problems with complex outputs are natural language parsing, sequence alignment in protein homology detection, and markov models for part-of-speech tagging. The SVMstruct algorithm can also be used for linear-time training of binary and multi-class SVMs under the linear kernel.
-SVMstruct is a Support Vector Machine (SVM) algorithm for predicting multivariate or structured outputs. It performs supervised learning by approximating a mapping
h: X--> Y
using labeled training examples (x1,y1), ..., (xn,yn). Unlike regular SVMs, however, which consider only univariate predictions like in classification and regression, SVMstruct can predict complex objects y like trees, sequences, or sets. Examples of problems with complex outputs are natural language parsing, sequence alignment in protein homology detection, and markov models for part-of-speech tagging. The SVMstruct algorithm can also be used for linear-time training of binary and multi-class SVMs under the linear kernel.
Platform: |
Size: 109568 |
Author:jon |
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Description: SVMstruct is a Support Vector Machine (SVM) algorithm for predicting multivariate or structured outputs. It performs supervised learning by approximating a mapping
h: X --> Y
using labeled training examples (x1,y1), ..., (xn,yn). Unlike regular SVMs, however, which consider only univariate predictions like in classification and regression, SVMstruct can predict complex objects y like trees, sequences, or sets. Examples of problems with complex outputs are natural language parsing, sequence alignment in protein homology detection, and markov models for part-of-speech tagging. The SVMstruct algorithm can also be used for linear-time training of binary and multi-class SVMs under the linear kernel.
-SVMstruct is a Support Vector Machine (SVM) algorithm for predicting multivariate or structured outputs. It performs supervised learning by approximating a mapping
h: X--> Y
using labeled training examples (x1,y1), ..., (xn,yn). Unlike regular SVMs, however, which consider only univariate predictions like in classification and regression, SVMstruct can predict complex objects y like trees, sequences, or sets. Examples of problems with complex outputs are natural language parsing, sequence alignment in protein homology detection, and markov models for part-of-speech tagging. The SVMstruct algorithm can also be used for linear-time training of binary and multi-class SVMs under the linear kernel.
Platform: |
Size: 117760 |
Author:jon |
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Description: 语音识别中的拒识算法和基于支持向量机的说话人识别技术研究，能够运行，希望对大家有用-Speech Recognition rejection algorithm and support vector machine based speech recognition technology, can run, we want to be useful Platform: |
Size: 2178048 |
Author:lifei |
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Description: 建立了普通话语音性别数据库,提出联合梅尔频率频谱系数(Mel2f requency Cep st rum
Coefficient s , MFCC) 的特征提取方法和支持向量机(Support Vector Machine , SVM) 的分类方法进行说话人性别识别,并与其它分类方法进行比较。-A Chinese speech ( mandarin ) database was established for speaker s gender recognition. A
combination met hod is p roposed for gender recognition of speaker s based on support vector machine and
Mel2f requency cep st rum coefficient s (MFCC) for classification and feat ure ext raction respectively. Platform: |
Size: 303104 |
Author:wangqipeng |
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Search - speech SUPPORT VECTOR MACHINE