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1. 发明授权

US07885456B2 Symbol graph generation in handwritten mathematical expression recognition 有权
标题翻译：手写数学表达式识别中的符号图生成
公开(公告)号：US07885456B2
公开(公告)日：2011-02-08
申请号：US11693299
申请日：2007-03-29
申请人： Yu Shi , Frank Kao-Ping Soong , Jian-Iai Zhou , Dongmei Zhang, legal representative
发明人： Yu Shi , Frank Kao-Ping Soong , Jian-Iai Zhou
IPC分类号： G06K9/00
CPC分类号： G06K9/6296 , G06K2209/01
摘要： A forward pass through a sequence of strokes representing a handwritten equation is performed from the first stroke to the last stroke in the sequence. At each stroke, a path score is determined for a plurality of symbol-relation pairs that each represents a symbol and its spatial relation to a predecessor symbol. A symbol graph having nodes and links is constructed by backtracking through the strokes from the last stroke to the first stroke and assigning scores to the links based on the path scores for the symbol-relation pairs. The symbol graph is used to recognize a mathematical expression based in part on the scores for the links and the mathematical expression is stored.
摘要翻译：从序列中的第一行程到最后一个行程执行表示手写方程的笔画序列的向前传递。在每个笔划处，确定多个符号 - 关系对的路径分数，每个符号 - 关系对都表示符号及其与前身符号的空间关系。具有节点和链接的符号图是通过从最后笔划到第一笔划的笔画回溯构成的，并且基于符号 - 关系对的路径得分将分数分配给链接。符号图用于部分地基于链接的分数来识别数学表达式，并存储数学表达式。

2. 发明申请

US20080243503A1 MINIMUM DIVERGENCE BASED DISCRIMINATIVE TRAINING FOR PATTERN RECOGNITION 审中-公开
标题翻译：最小的基于分歧的歧视识别训练
公开(公告)号：US20080243503A1
公开(公告)日：2008-10-02
申请号：US11694375
申请日：2007-03-30
申请人： Frank Kao-Ping Soong , Peng Liu , Jian-Iai Zhou , Dongmei Zhang
发明人： Frank Kao-Ping Soong , Peng Liu , Jian-Iai Zhou , Dongmei Zhang
IPC分类号： G10L15/06
CPC分类号： G10L15/063
摘要： A method of providing discriminative training of a speech recognition unit is discussed. The method includes receiving an acoustic indication of an utterance having a hypothesis space and comparing the hypothesis space against a reference. The method measures the Kullback-Leibler Divergence (KLD) between the reference and the hypothesis space to adjust the reference and stores the adjusted reference on a tangible storage medium.
摘要翻译：讨论了提供语音识别单元的辨别性训练的方法。该方法包括接收具有假设空间的话语的声学指示，并将假设空间与参考值进行比较。该方法测量参考和假设空间之间的Kullback-Leibler发散（KLD）以调整参考，并将调整的参考存储在有形存储介质上。

3. 发明申请

US20090245646A1 Online Handwriting Expression Recognition 审中-公开
标题翻译：在线手写表达识别
公开(公告)号：US20090245646A1
公开(公告)日：2009-10-01
申请号：US12058506
申请日：2008-03-28
申请人： Yu Shi , Frank Kao-Ping Soong
发明人： Yu Shi , Frank Kao-Ping Soong
IPC分类号： G06K9/78
CPC分类号： G06K9/00422 , G06K9/00879
摘要： One way of recognizing online handwritten mathematical expressions is to use a one-pass dynamic programming based symbol decoding generation algorithm. This method embeds segmentation into symbol identification to form a unified framework for symbol recognition. Along with decoding, a symbol graph is produced. Besides accurately recognizing handwritten mathematical expressions, this method can produce high quality symbol graphs. This method uses six knowledge source models to help search for possible symbol hypotheses during the decoding process. Here, knowledge source exponential weights and a symbol insertion penalty are used to weigh the various knowledge source model probabilities to increase accuracy.
摘要翻译：识别在线手写数学表达式的一种方法是使用基于单程动态规划的符号解码生成算法。该方法将分段嵌入符号识别中，形成符号识别的统一框架。随着解码，产生符号图。除了精确地识别手写数学表达，这种方法可以产生高质量的符号图。该方法使用六种知识源模型来帮助在解码过程中搜索可能的符号假设。这里，知识源指数权重和符号插入罚分用于权衡各种知识源模型概率以提高准确性。

4. 发明申请

US20100166314A1 Segment Sequence-Based Handwritten Expression Recognition 审中-公开
标题翻译：基于片段序列的手写表达识别
公开(公告)号：US20100166314A1
公开(公告)日：2010-07-01
申请号：US12346376
申请日：2008-12-30
申请人： Yu Shi , Frank Kao-Ping Soong
发明人： Yu Shi , Frank Kao-Ping Soong
IPC分类号： G06K9/00
CPC分类号： G06K9/00422 , G06K9/6296
摘要： Methods and apparatuses for generating, by a computing device configured to interpret a handwritten expression, a symbol graph to represent strokes associated with the handwritten expression, are described herein. The symbol graph may include nodes, each node corresponding to a combination of a stroke and a candidate symbol for that stroke. The computing device may also generate a segment graph based on the symbol graph by combining nodes associated with a same stroke if strokes of their preceding nodes are the same. Also the computing device may perform a structure analysis on at least a subset of segment sequences represented by the segment graph to determine hypotheses for the handwritten expression. In other embodiments, rather than generate a segment graph, the computing device may determine segment sequences by selecting a number of symbol sequences from the symbol graph and combining symbol sequences having the same segmentation.
摘要翻译：本文描述了通过被配置为解读手写表达式的计算设备来生成表示与手写表达式相关联的笔画的符号图形的方法和装置。符号图可以包括节点，每个节点对应于笔划的组合和该笔划的候选符号。如果其前面的节点的笔划相同，则计算设备还可以通过组合与相同笔划相关联的节点来基于该符号图来生成片段图。此外，计算设备还可以对由片段图表示的段序列的至少一个子集进行结构分析，以确定手写表达式的假设。在其他实施例中，计算设备可以通过从符号图中选择符号序列的数目并组合具有相同分割的符号序列来确定段序列而不是生成段图。

5. 发明申请

US20080240570A1 SYMBOL GRAPH GENERATION IN HANDWRITTEN MATHEMATICAL EXPRESSION RECOGNITION 有权
标题翻译：手工数学表达识别中的符号图生成
公开(公告)号：US20080240570A1
公开(公告)日：2008-10-02
申请号：US11693299
申请日：2007-03-29
申请人： Yu Shi , Frank Kao-Ping Soong , Jian-lai Zhou , Dongmei Zhang
发明人： Yu Shi , Frank Kao-Ping Soong , Jian-lai Zhou , Dongmei Zhang
IPC分类号： G06K9/00
CPC分类号： G06K9/6296 , G06K2209/01
摘要： A forward pass through a sequence of strokes representing a handwritten equation is performed from the first stroke to the last stroke in the sequence. At each stroke, a path score is determined for a plurality of symbol-relation pairs that each represents a symbol and its spatial relation to a predecessor symbol. A symbol graph having nodes and links is constructed by backtracking through the strokes from the last stroke to the first stroke and assigning scores to the links based on the path scores for the symbol-relation pairs. The symbol graph is used to recognize a mathematical expression based in part on the scores for the links and the mathematical expression is stored.
摘要翻译：从序列中的第一行程到最后一个行程执行表示手写方程的笔画序列的向前传递。在每个笔划处，确定多个符号 - 关系对的路径分数，每个符号 - 关系对都表示符号及其与前身符号的空间关系。具有节点和链接的符号图是通过从最后笔划到第一笔划的笔画回溯构成的，并且基于符号 - 关系对的路径得分将分数分配给链接。符号图用于部分地基于链接的分数来识别数学表达式，并存储数学表达式。

6. 发明申请

US20080189109A1 Segmentation posterior based boundary point determination 审中-公开
标题翻译：分段后验边界点确定
公开(公告)号：US20080189109A1
公开(公告)日：2008-08-07
申请号：US11702373
申请日：2007-02-05
申请人： Yu Shi , Frank Kao-Ping Soong
发明人： Yu Shi , Frank Kao-Ping Soong
IPC分类号： G10L15/00
CPC分类号： G10L15/04
摘要： Boundary points for speech in an audio signal are determined based on posterior probabilities for the boundary points given a set of possible segmentations of the audio signal. The boundary point posterior probability is determined based on a set of level posterior probabilities that each provide the probability of a sequence of feature vectors given one of the segmentations in the set of possible segmentations.
摘要翻译：基于给定一组可能的音频信号分段的边界点的后验概率来确定音频信号中的语音的边界点。基于一组级别后验概率来确定边界点后验概率，每组提供一组特征向量的概率，该特征向量在可能的分段集合中给出一个分段。

7. 发明授权

US10319363B2 Audio human interactive proof based on text-to-speech and semantics 有权
公开(公告)号：US10319363B2
公开(公告)日：2019-06-11
申请号：US13399496
申请日：2012-02-17
申请人： Yao Qian , Frank Kao-Ping Soong , Bin Benjamin Zhu
发明人： Yao Qian , Frank Kao-Ping Soong , Bin Benjamin Zhu
IPC分类号： G10L13/033 , G10L21/003 , G10L15/00
摘要： The text-to-speech audio HIP technique described herein in some embodiments uses different correlated or uncorrelated words or sentences generated via a text-to-speech engine as audio HIP challenges. The technique can apply different effects in the text-to-speech synthesizer speaking a sentence to be used as a HIP challenge string. The different effects can include, for example, spectral frequency warping; vowel duration warping; background addition; echo addition; and varying the time duration between words, among others. In some embodiments the technique varies the set of parameters to prevent using Automated Speech Recognition tools from using previously used audio HIP challenges to learn a model which can then be used to recognize future audio HIP challenges generated by the technique. Additionally, in some embodiments the technique introduces the requirement of semantic understanding in HIP challenges.

8. 发明申请

US20140025381A1 EVALUATING TEXT-TO-SPEECH INTELLIGIBILITY USING TEMPLATE CONSTRAINED GENERALIZED POSTERIOR PROBABILITY 审中-公开
标题翻译：使用模板约束的一般化后验概率评估文本到语音智能
公开(公告)号：US20140025381A1
公开(公告)日：2014-01-23
申请号：US13554480
申请日：2012-07-20
申请人： Linfang Wang , Yan Teng , Lijuan Wang , Frank Kao-Ping Soong , Zhe Geng , William Brad Waller , Mark Tillman Hanson
发明人： Linfang Wang , Yan Teng , Lijuan Wang , Frank Kao-Ping Soong , Zhe Geng , William Brad Waller , Mark Tillman Hanson
IPC分类号： G10L13/08
CPC分类号： G10L25/69 , G10L13/00
摘要： Instead of relying on humans to subjectively evaluate speech intelligibility of a subject, a system objectively evaluates the speech intelligibility. The system receives speech input and calculates confidence scores at multiple different levels using a Template Constrained Generalized Posterior Probability algorithm. One or multiple intelligibility classifiers are utilized to classify the desired entities on an intelligibility scale. A specific intelligibility classifier utilizes features such as the various confidence scores. The scale of the intelligibility classification can be adjusted to suit the application scenario. Based on the confidence score distributions and the intelligibility classification results at multiple levels an overall objective intelligibility score is calculated. The objective intelligibility scores can be used to rank different subjects or systems being assessed according to their intelligibility levels. The speech that is below a predetermined intelligibility (e.g. utterances with low confidence scores and most severe intelligibility issues) can be automatically selected for further analysis.
摘要翻译：系统客观地评估语言的可懂度，而不是依靠人类来主观地评估一个主题的语音清晰度。系统接收语音输入，并使用模板约束广义后验概率算法在多个不同级别计算置信度分数。一个或多个可理解性分类器用于在可懂度量表上分类所需实体。特定的清晰度分类器利用各种置信度分数等特征。可以调整可懂度分类的规模，以适应应用场景。基于多个级别的置信度分数和可理解性分类结果，计算出总目标可懂度分数。客观可理解性分数可用于根据其可理解性级别对待评估的不同科目或系统进行排名。可以自动选择低于预定清晰度（例如具有低置信度得分和最严重的可理解性问题的话语）的语音用于进一步分析。

9. 发明授权

US07496513B2 Combined input processing for a computing device 有权
标题翻译：用于计算设备的组合输入处理
公开(公告)号：US07496513B2
公开(公告)日：2009-02-24
申请号：US11168279
申请日：2005-06-28
申请人： Frank Kao-Ping Soong , Jian-Lai Zhou , Ye Tian
发明人： Frank Kao-Ping Soong , Jian-Lai Zhou , Ye Tian
IPC分类号： G06K9/18 , G10L13/08 , G10L15/00 , G06F3/00 , G06F3/048
CPC分类号： G06F3/038 , G06F3/0237 , G06F3/04883 , G06F2203/0381
摘要： Input is received from at least two different input sources. Information from these sources are combined together to provide a result. In a particular example, input from one source corresponds to potential recognition candidates, and input from another source corresponds to other potential candidates. These candidates are combined together to select a result.
摘要翻译：从至少两个不同的输入源接收输入。来自这些来源的信息被组合在一起以提供结果。在特定示例中，来自一个源的输入对应于潜在的识别候选，并且来自另一个源的输入对应于其他潜在候选。将这些候选人组合在一起以选择结果。

10. 发明申请

US20080195381A1 Line Spectrum pair density modeling for speech applications 审中-公开
标题翻译：用于语音应用的线谱对密度建模
公开(公告)号：US20080195381A1
公开(公告)日：2008-08-14
申请号：US11704522
申请日：2007-02-09
申请人： Frank Kao-Ping Soong , Yao Qian
发明人： Frank Kao-Ping Soong , Yao Qian
IPC分类号： G10L11/00
CPC分类号： G10L25/48
摘要： Novel techniques for providing superior performance and sound quality in speech applications, such as speech synthesis, speech coding, and automatic speech recognition, are hereby disclosed. In one illustrative embodiment, a method includes modeling a speech signal with parameters comprising line spectrum pairs. Density parameters are provided based on the density of the line spectrum pairs. A speech application output, such as synthesized speech, is provided based at least in part on the line spectrum pair density parameters. The line spectrum pair density parameters use computing resources efficiently while providing improved performance and sound quality in the speech application output.
摘要翻译：特此公开了用于在诸如语音合成，语音编码和自动语音识别等语音应用中提供卓越性能和声音质量的新技术。在一个说明性实施例中，一种方法包括用包括线谱对的参数对语音信号进行建模。基于线谱对的密度提供密度参数。至少部分地基于线谱对密度参数来提供诸如合成语音的语音应用输出。线谱对密度参数有效利用计算资源，同时在语音应用输出中提供改进的性能和声音质量。

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