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    • 41. 发明授权
    • Gaming headset and charging method
    • 游戏耳机和充电方式
    • US08355515B2
    • 2013-01-15
    • US12099046
    • 2008-04-07
    • Xiadong MaoRuxin ChenSeth C. H. Luisi
    • Xiadong MaoRuxin ChenSeth C. H. Luisi
    • H04R1/10H04R25/00H04M1/00H04M9/00
    • H04R1/1025H04R1/1041H04R3/005H04R2201/107H04R2205/021H04R2420/03H04R2420/07
    • An audio headset may comprise a case, near field microphone and far field microphone. A speaker, processor, memory, battery, charging interface and cradle detection circuit may be mounted to the case. Processor-executable instructions embodied in the memory, may be configured to implement a battery charging method. The headset may be shut off in response to placement of the headset in a charging cradle. The far-field microphone is turned on but not the near-field microphone. The battery may then be charged from the cradle. A headset having near-field and far-field microphones may be used to distinguish between user speech and competing sounds by generating signals from the sounds detected by each microphone and comparing the strengths of the signals. The signals may be processed as user speech if they are of comparable strength. Otherwise, the near-field signal may be processed as user speech and the far-field signal as competing sounds.
    • 音频耳机可以包括外壳,近场麦克风和远场麦克风。 扬声器,处理器,存储器,电池,充电接口和支架检测电路可以安装在壳体上。 在存储器中体现的处理器可执行指令可以被配置为实现电池充电方法。 耳机可以响应于将耳机放置在充电座中而被关闭。 远场麦克风开启,但不是近场麦克风。 然后电池可以从支架充电。 具有近场和远场麦克风的耳机可用于通过从由每个麦克风检测到的声音产生信号并比较信号的强度来区分用户语音和竞争声音。 如果信号具有可比较的强度,那么信号可以被用作用户语音。 否则,可以将近场信号作为用户语音处理,将远场信号作为竞争声音进行处理。
    • 44. 发明授权
    • Structure for grammar and dictionary representation in voice recognition and method for simplifying link and node-generated grammars
    • 用于语音识别中的语法和字典表示的结构以及用于简化链接和节点生成的语法的方法
    • US07921011B2
    • 2011-04-05
    • US11437444
    • 2006-05-19
    • Gustavo Hernandez AbregoRuxin Chen
    • Gustavo Hernandez AbregoRuxin Chen
    • G10L15/04G10L15/18G06F17/20
    • G10L15/193G10L15/285
    • Methods for optimizing grammar structure for a set of phrases to be used in speech recognition during a computing event are provided. One method includes receiving a set of phrases, the set of phrases being relevant for the computing event and the set of phrases having a node and link structure. Also included is identifying redundant nodes by examining the node and link structures of each of the set of phrases so as to generate a single node for the redundant nodes. The method further includes examining the node and link structures to identify nodes that are capable of being vertically grouped and grouping the identified nodes to define vertical word groups. The method continues with fusing nodes of the set of phrases that are not vertically grouped into fused word groups. Wherein the vertical word groups and the fused word groups are linked to define an optimized grammar structure. In another aspect, a layered grammar and dictionary library that can be defined for efficient use in speech recognition systems, is provided.
    • 提供了一种用于在计算事件期间用于语音识别中的一组短语的语法结构优化的方法。 一种方法包括接收一组短语,该组短语与计算事件相关,以及具有节点和链接结构的短语集合。 还包括通过检查每组短语的节点和链接结构来识别冗余节点,以便为冗余节点生成单个节点。 该方法还包括检查节点和链路结构以识别能够被垂直分组的节点,并且对所识别的节点进行分组以定义垂直字组。 该方法继续融合未垂直分组成融合词组的短语集合中的节点。 其中垂直单词组和融合词组被链接以定义优化的语法结构。 在另一方面,提供了可以被定义用于语音识别系统中有效使用的分层语法和字典库。
    • 45. 发明申请
    • METHOD AND SYSTEM FOR MODELING A COMMON-LANGUAGE SPEECH RECOGNITION, BY A COMPUTER, UNDER THE INFLUENCE OF A PLURALITY OF DIALECTS
    • 在大量对话的影响下,由计算机建模常见语音识别的方法和系统
    • US20100121640A1
    • 2010-05-13
    • US12608191
    • 2009-10-29
    • Fang ZhengXi XiaoLinquan LiuZhan YouWenxiao CaoMakoto AkabaneRuxin ChenYoshikazu Takahashi
    • Fang ZhengXi XiaoLinquan LiuZhan YouWenxiao CaoMakoto AkabaneRuxin ChenYoshikazu Takahashi
    • G10L15/06G10L15/00
    • G10L15/187
    • The present invention relates to a method for modeling a common-language speech recognition, by a computer, under the influence of multiple dialects and concerns a technical field of speech recognition by a computer. In this method, a triphone standard common-language model is first generated based on training data of standard common language, and first and second monophone dialectal-accented common-language models are based on development data of dialectal-accented common languages of first kind and second kind, respectively. Then a temporary merged model is obtained in a manner that the first dialectal-accented common-language model is merged into the standard common-language model according to a first confusion matrix obtained by recognizing the development data of first dialectal-accented common language using the standard common-language model. Finally, a recognition model is obtained in a manner that the second dialectal-accented common-language model is merged into the temporary merged model according to a second confusion matrix generated by recognizing the development data of second dialectal-accented common language by the temporary merged model. This method effectively enhances the operating efficiency and admittedly raises the recognition rate for the dialectal-accented common language. The recognition rate for the standard common language is also raised.
    • 本发明涉及一种通过计算机在多种方言的影响下对共同语言语音识别进行建模的方法,并涉及计算机的语音识别技术领域。 在这种方法中,首先基于标准通用语言的训练数据生成三通电话标准通用语言模型,第一和第二单音方言重点共同语言模型基于第一种方言重音通用语言的开发数据, 第二类。 然后按照第一个方言重音的共同语言模型按照第一个混淆矩阵将第一个方言重音的共同语言模型合并到第一个混淆矩阵中的方式获得临时合并模型,该第一混淆矩阵通过使用 标准通用语言模型。 最后,根据通过临时合并识别第二方言重音的共同语言的开发数据产生的第二混淆矩阵,将第二方言重音的共同语言模型合并到临时合并模型中,获得识别模型 模型。 这种方法有效提高了运营效率,并且提高了方言重音普通语言的识别率。 标准通用语言的识别率也提高了。
    • 48. 发明申请
    • Structure for grammar and dictionary representation in voice recognition and method for simplifying link and node-generated grammars
    • 用于语音识别中的语法和字典表示的结构以及用于简化链接和节点生成的语法的方法
    • US20060277032A1
    • 2006-12-07
    • US11437444
    • 2006-05-19
    • Gustavo Hernandez-AbregoRuxin Chen
    • Gustavo Hernandez-AbregoRuxin Chen
    • G06F17/27
    • G10L15/193G10L15/285
    • Methods for optimizing grammar structure for a set of phrases to be used in speech recognition during a computing event are provided. One method includes receiving a set of phrases, the set of phrases being relevant for the computing event and the set of phrases having a node and link structure. Also included is identifying redundant nodes by examining the node and link structures of each of the set of phrases so as to generate a single node for the redundant nodes. The method further includes examining the node and link structures to identify nodes that are capable of being vertically grouped and grouping the identified nodes to define vertical word groups. The method continues with fusing nodes of the set of phrases that are not vertically grouped into fused word groups. Wherein the vertical word groups and the fused word groups are linked to define an optimized grammar structure. In another aspect, a layered grammar and dictionary library that can be defined for efficient use in speech recognition systems, is provided.
    • 提供了一种用于在计算事件期间用于语音识别中的一组短语的语法结构优化的方法。 一种方法包括接收一组短语,该组短语与计算事件相关,以及具有节点和链接结构的短语集合。 还包括通过检查每组短语的节点和链接结构来识别冗余节点,以便为冗余节点生成单个节点。 该方法还包括检查节点和链路结构以识别能够被垂直分组的节点,并且对所识别的节点进行分组以定义垂直字组。 该方法继续融合未垂直分组成融合词组的短语集合中的节点。 其中垂直单词组和融合词组被链接以定义优化的语法结构。 在另一方面,提供了可以被定义用于语音识别系统中有效使用的分层语法和字典库。
    • 49. 发明授权
    • Text dependent speaker recognition with long-term feature based on functional data analysis
    • 基于功能数据分析的具有长期特征的文本相关扬声器识别
    • US09153235B2
    • 2015-10-06
    • US13799647
    • 2013-03-13
    • Chenhao ZhangRuxin ChenThomas Fang Zheng
    • Chenhao ZhangRuxin ChenThomas Fang Zheng
    • G10L17/00G10L17/02G10L17/08G10L17/24
    • G10L17/00G10L17/02G10L17/08G10L17/24
    • One or more test features are extracted from a time domain signal. The test features are represented by discrete data. The discrete data is represented for each of the one or more test features by a corresponding one or more fitting functions, which are defined in terms of finite number of continuous basis functions and a corresponding finite number of expansion coefficients. Each fitting function is compressed through Functional Principal Component Analysis (FPCA) to generate corresponding sets of principal components. Each principal component for a given test feature is uncorrelated to each other principal component for the given test feature. A distance between a set of principal components for the given test feature and a set of principal components for one or more training features with the processing system is calculated. The test feature is classified according to the distance calculated with the processing system.
    • 从时域信号中提取一个或多个测试特征。 测试特征由离散数据表示。 通过相应的一个或多个拟合函数为一个或多个测试特征中的每一个表示离散数据,其根据有限数量的连续基函数和对应的有限数量的扩展系数来定义。 每个拟合函数通过功能主成分分析(FPCA)进行压缩,以生成相应的主成分组。 给定测试特征的每个主要组件与给定测试特征的每个主要组件不相关。 计算给定测试特征的一组主要组件与处理系统的一个或多个训练特征的一组主要组件之间的距离。 测试功能根据处理系统计算的距离进行分类。