Description: This class library contains more than 20 classes including feature extraction algorithms (MFCC, LPCC) and modeling techniques (HMM, GMM, DTW, VQ ) for automatic speech recognition and speaker verification Platform: |
Size: 1406163 |
Author:站长 |
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Description: Currently, there are more than 20 classes in this library,
including commonly used feature extraction algorithms and
modeling techniques for speech recognition and speaker verification. -Currently, there are more than 20 classes in this library. including commonly used feature extraction al gorithms and modeling techniques for re speech cognition and speaker verification. Platform: |
Size: 1127171 |
Author:原琴 |
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Description: This class library contains more than 20 classes including feature extraction algorithms (MFCC, LPCC) and modeling techniques (HMM, GMM, DTW, VQ ) for automatic speech recognition and speaker verification Platform: |
Size: 1405952 |
Author:站长 |
Hits:
Description: Currently, there are more than 20 classes in this library,
including commonly used feature extraction algorithms and
modeling techniques for speech recognition and speaker verification. -Currently, there are more than 20 classes in this library. including commonly used feature extraction al gorithms and modeling techniques for re speech cognition and speaker verification. Platform: |
Size: 1126400 |
Author:原琴 |
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Description: 在本文中,主要讲了在语音识别和语音合成之前我们所要做的主要工作，包括去噪,预加重,端点检测,特征参数提取等技术.-In this article, the main speaker in the speech recognition and speech synthesis to be done before we have major work, including de-noising, pre-emphasis, endpoint detection, feature extraction techniques. Platform: |
Size: 3084288 |
Author:chengbin |
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Description: 语音识别技术主要包括特征提取技术、模式匹配准则及模型训练技术三个方面。此外，还涉及到语音识别单元的选取。选择识别单元是语音识别研究的第一步。语音识别单元有单词（句）、音节和音素三种，具体选择哪一种，由具体的研究任务决定。-Speech recognition technology, including feature extraction techniques, pattern-matching criteria and the three aspects of model training techniques. In addition, it involves the selection of speech recognition modules. Choose identification unit is the first step in speech recognition research. Speech recognition module has the word (sentence), three types of syllables and phonemes, the specific selection of which, by the specific research mission decide. Platform: |
Size: 8192 |
Author:candy |
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Description: 这个是用Matlab写成的说话人识别演示程序。-Currently, there are more than 20 classes in this library, including commonly used feature extraction algorithms and modeling techniques for speech recognition and speaker verification.-Currently, there are more than 20 classes in this library. including commonly used feature extraction al gorithms and modeling techniques for re speech cognition and speaker verification. Platform: |
Size: 2451456 |
Author:liximin |
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Description: Abstract—This paper proposes a new technique for face detection
and lip feature extraction. A real-time field-programmable
gate array (FPGA) implementation of the two proposed techniques
is also presented. Face detection is based on a naive Bayes classifier
that classifies an edge-extracted representation of an image. Using
edge representation significantly reduces the model’s size to only
5184 B, which is 2417 times smaller than a comparable statistical
modeling technique, while achieving an 86.6 correct detection
rate under various lighting conditions. Lip feature extraction uses
the contrast around the lip contour to extract the height and width
of the mouth, metrics that are useful for speech filtering. The
proposed FPGA system occupies only 15 050 logic cells, or about
six times less than a current comparable FPGA face detection
system.-Abstract—This paper proposes a new technique for face detection
and lip feature extraction. A real-time field-programmable
gate array (FPGA) implementation of the two proposed techniques
is also presented. Face detection is based on a naive Bayes classifier
that classifies an edge-extracted representation of an image. Using
edge representation significantly reduces the model’s size to only
5184 B, which is 2417 times smaller than a comparable statistical
modeling technique, while achieving an 86.6 correct detection
rate under various lighting conditions. Lip feature extraction uses
the contrast around the lip contour to extract the height and width
of the mouth, metrics that are useful for speech filtering. The
proposed FPGA system occupies only 15 050 logic cells, or about
six times less than a current comparable FPGA face detection
system. Platform: |
Size: 28409856 |
Author:ramanaidu |
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Search - speech feature extraction techniques