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71. 发明申请

US20090180695A1 ASYMMETRIC SCORE NORMALIZATION FOR HANDWRITTEN WORD SPOTTING SYSTEM 有权
标题翻译：用于手写字体系统的不对称分数正规化
公开(公告)号：US20090180695A1
公开(公告)日：2009-07-16
申请号：US12014193
申请日：2008-01-15
申请人： Jose A. Rodriguez Serrano , Florent Perronnin
发明人： Jose A. Rodriguez Serrano , Florent Perronnin
IPC分类号： G06K9/00
CPC分类号： G06K9/00879 , G06K9/6292
摘要： A method begins by receiving an image of a handwritten item. The method performs a word segmentation process on the image to produce a sub-image and extracts a set of feature vectors from the sub-image. Then, the method performs an asymmetric approach that computes a first log-likelihood score of the feature vectors using a word model having a first structure (such as one comprising a Hidden Markov Model (HMM)) and also computes a second log-likelihood score of the feature vectors using a background model having a second structure (such as one comprising a Gaussian Mixture Model (GMM)). The method computes a final score for the sub-image by subtracting the second log-likelihood score from the first log-likelihood score. The final score is then compared against a predetermined standard to produce a word identification result and the word identification result is output.
摘要翻译：方法从接收手写物品的图像开始。该方法对图像执行字分割处理以产生子图像，并从子图像提取一组特征向量。然后，该方法执行非对称方法，其使用具有第一结构（诸如包括隐马尔可夫模型（HMM）的单词）的单词模型来计算特征向量的第一对数似然分数，并且还计算第二对数似然分数的特征向量使用具有第二结构的背景模型（例如包括高斯混合模型（GMM）的背景模型））。该方法通过从第一对数似然分数中减去第二对数似然分数来计算子图像的最终得分。然后将最终得分与预定标准进行比较以产生字识别结果，并输出字识别结果。

72. 发明申请

US20070005356A1 Generic visual categorization method and system 有权
标题翻译：一般视觉分类方法和系统
公开(公告)号：US20070005356A1
公开(公告)日：2007-01-04
申请号：US11170496
申请日：2005-06-30
申请人： Florent Perronnin
发明人： Florent Perronnin
IPC分类号： G10L15/06
CPC分类号： G06K9/4676
摘要： Generic visual categorization methods complement a general vocabulary with adapted vocabularies that are class specific. Images to be categorized are characterized within different categories through a histogram indicating whether the image is better described by the general vocabulary or the class-specific adapted vocabulary.
摘要翻译：通用视觉分类方法补充了具有类特定的适应词汇的一般词汇。要分类的图像通过直方图表征不同的类别，该直方图指示图像是否被一般词汇表或类别特定的适应词汇表更好地描述。

73. 发明授权

US06895376B2 Eigenvoice re-estimation technique of acoustic models for speech recognition, speaker identification and speaker verification 有权
标题翻译：用于语音识别，扬声器识别和说话人验证的声学模型的本征语重新估计技术
公开(公告)号：US06895376B2
公开(公告)日：2005-05-17
申请号：US09849174
申请日：2001-05-04
申请人： Florent Perronnin , Roland Kuhn , Patrick Nguyen , Jean-Claude Junqua
发明人： Florent Perronnin , Roland Kuhn , Patrick Nguyen , Jean-Claude Junqua
IPC分类号： G10L15/06 , G10L17/00
CPC分类号： G10L15/07 , G10L17/02
摘要： A reduced dimensionality eigenvoice analytical technique is used during training to develop context-dependent acoustic models for allophones. Re-estimation processes are performed to more strongly separate speaker-dependent and speaker-independent components of the speech model. The eigenvoice technique is also used during run time upon the speech of a new speaker. The technique removes individual speaker idiosyncrasies, to produce more universally applicable and robust allophone models. In one embodiment the eigenvoice technique is used to identify the centroid of each speaker, which may then be “subtracted out” of the recognition equation.
摘要翻译：在训练期间使用减小的维度本征语音分析技术来开发用于异音素的上下文相关的声学模型。执行重新估计过程以更强烈地分离语音模型的与扬声器相关的和与扬声器无关的组件。特定语音技术在运行时也用于新演讲者的演讲。该技术可以消除单个扬声器的特性，从而产生更普遍适用和强大的异音模型。在一个实施例中，本征语音技术用于识别每个说话者的质心，然后可以将其“减去”识别方程。

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