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    • 51. 发明授权
    • Optimization of natural language processing system based on conditional output quality at risk
    • 基于条件输出质量风险的自然语言处理系统优化
    • US08660836B2
    • 2014-02-25
    • US13073255
    • 2011-03-28
    • Vittorio CastelliDavid NahamooBing Zhao
    • Vittorio CastelliDavid NahamooBing Zhao
    • G10L15/00
    • G06F17/2818G06F17/2854
    • Techniques are disclosed for optimizing results output by a natural language processing system. For example, a method comprises optimizing one or more parameters of a natural language processing system so as to improve a measure of quality of an output of the natural language processing system for a first type of data processed by the natural language processing system while maintaining a given measure of quality of an output of the natural language processing system for a second type of data processed by the natural language processing system. For example, the first type of data may have a substantive complexity that is greater than that of the second type of data. Thus, when the natural language processing system is a machine translation system, use of a conditional value at risk metric for the translation quality provides for a high quality output of the machine translation system for data of a high substantive complexity (for sophisticated users) while maintaining an average quality output for average data (for average users).
    • 公开了用于优化由自然语言处理系统输出的结果的技术。 例如,一种方法包括优化自然语言处理系统的一个或多个参数,以便改善对于由自然语言处理系统处理的第一类型的数据的自然语言处理系统的输出的质量的量度,同时保持 给出自然语言处理系统对自然语言处理系统处理的第二类数据的输出质量的度量。 例如,第一类型的数据可能具有大于第二类型的数据的实质性复杂度。 因此,当自然语言处理系统是机器翻译系统时,使用翻译质量的风险度量条件值为机器翻译系统提供高质量的高实质性复杂性(针对复杂用户)的数据输出,同时 维持平均数据(平均用户)的平均质量输出。
    • 53. 发明申请
    • OPTIMIZATION OF NATURAL LANGUAGE PROCESSING SYSTEM BASED ON CONDITIONAL OUTPUT QUALITY AT RISK
    • 基于条件输出质量风险的自然语言处理系统优化
    • US20120253783A1
    • 2012-10-04
    • US13073255
    • 2011-03-28
    • Vittorio CastelliDavid NahamooBing Zhao
    • Vittorio CastelliDavid NahamooBing Zhao
    • G06F17/28G06F17/27
    • G06F17/2818G06F17/2854
    • Techniques are disclosed for optimizing results output by a natural language processing system. For example, a method comprises optimizing one or more parameters of a natural language processing system so as to improve a measure of quality of an output of the natural language processing system for a first type of data processed by the natural language processing system while maintaining a given measure of quality of an output of the natural language processing system for a second type of data processed by the natural language processing system. For example, the first type of data may have a substantive complexity that is greater than that of the second type of data. Thus, when the natural language processing system is a machine translation system, use of a conditional value at risk metric for the translation quality provides for a high quality output of the machine translation system for data of a high substantive complexity (for sophisticated users) while maintaining an average quality output for average data (for average users).
    • 公开了用于优化由自然语言处理系统输出的结果的技术。 例如,一种方法包括优化自然语言处理系统的一个或多个参数,以便改善对于由自然语言处理系统处理的第一类型的数据的自然语言处理系统的输出的质量的量度,同时保持 给出自然语言处理系统对自然语言处理系统处理的第二类数据的输出质量的度量。 例如,第一类型的数据可能具有大于第二类型的数据的实质性复杂度。 因此,当自然语言处理系统是机器翻译系统时,使用翻译质量的风险度量条件值为机器翻译系统提供高质量的高实质性复杂性(针对复杂用户)的数据输出,同时 维持平均数据(平均用户)的平均质量输出。
    • 54. 发明申请
    • VOICE TRANSFORMATION WITH ENCODED INFORMATION
    • 语音转换与编码信息
    • US20120239387A1
    • 2012-09-20
    • US13049924
    • 2011-03-17
    • Shay Ben-DavidRon HooryZvi KonsDavid Nahamoo
    • Shay Ben-DavidRon HooryZvi KonsDavid Nahamoo
    • G10L19/02
    • G10L21/003G10L19/018
    • Method, system, and computer program product for voice transformation are provided. The method includes transforming a source speech using transformation parameters, and encoding information on the transformation parameters in an output speech using steganography, wherein the source speech can be reconstructed using the output speech and the information on the transformation parameters. A method for reconstructing voice transformation is also provided including: receiving an output speech of a voice transformation system wherein the output speech is transformed speech which has encoded information on the transformation parameters using steganography; extracting the information on the transformation parameters; and carrying out an inverse transformation of the output speech to obtain an approximation of an original source speech.
    • 提供语音转换的方法,系统和计算机程序产品。 该方法包括使用变换参数来变换源语言,以及使用隐写术对输入语音中的变换参数对信息进行编码,其中可以使用输出语音和关于变换参数的信息来重构源语音。 还提供了一种用于重建语音变换的方法,包括:接收语音转换系统的输出语音,其中输出语音是使用隐写术编码关于变换参数的信息的变换语音; 提取变换参数信息; 并执行输出语音的逆变换以获得原始源语音的近似。
    • 55. 发明授权
    • Conversational computing via conversational virtual machine
    • 通过对话虚拟机进行会话计算
    • US07137126B1
    • 2006-11-14
    • US09806565
    • 1999-10-01
    • Daniel CoffmanLiam D. ComerfordSteven DeGennaroEdward A. EpsteinPonani GopalakrishnanStephane H. MaesDavid Nahamoo
    • Daniel CoffmanLiam D. ComerfordSteven DeGennaroEdward A. EpsteinPonani GopalakrishnanStephane H. MaesDavid Nahamoo
    • G06F9/54G06F9/50G06F9/44G10L15/00
    • H04M3/50G06F17/30899G10L15/22G10L15/285G10L2015/228H04L67/02H04M1/72561H04M3/42204H04M3/44H04M3/493H04M3/4931H04M3/4936H04M3/4938H04M7/00H04M2201/40H04M2201/60H04M2203/355H04M2250/74
    • A conversational computing system that provides a universal coordinated multi-modal conversational user interface (CUI) (10) across a plurality of conversationally aware applications (11) (i.e., applications that “speak” conversational protocols) and conventional applications (12). The conversationally aware maps, applications (11) communicate with a conversational kernel (14) via conversational application APIs (13). The conversational kernel (14) controls the dialog across applications and devices (local and networked) on the basis of their registered conversational capabilities and requirements and provides a unified conversational user interface and conversational services and behaviors. The conversational computing system may be built on top of a conventional operating system and APIs (15) and conventional device hardware (16). The conversational kernel (14) handles all I/O processing and controls conversational engines (18). The conversational kernel (14) converts voice requests into queries and converts outputs and results into spoken messages using conversational engines (18) and conversational arguments (17). The conversational application API (13) conveys all the information for the conversational kernel (14) to transform queries into application calls and conversely convert output into speech, appropriately sorted before being provided to the user.
    • 一种对话计算系统,其跨越多个会话感知应用(11)(即,“说”对话协议的应用“)和常规应用(12)提供通用协调多模态对话用户界面(CUI)(10)。 对话感知地图,应用程序(11)通过对话应用程序API(13)与对话内核(14)进行通信。 对话内核(14)根据其注册的会话能力和要求,控制应用和设备(本地和网络)之间的对话,并提供统一的会话用户界面和对话服务和行为。 对话计算系统可以构建在常规操作系统和API(15)和常规设备硬件(16)之上。 对话内核(14)处理所有I / O处理和控制对话引擎(18)。 会话内核(14)将语音请求转换为查询,并将会话引擎(18)和会话参数(17)将输出和结果转换为口语消息。 对话应用程序API(13)传达对话内核(14)的所有信息,以将查询转换成应用程序调用,并相反地将输出转换为语音,在提供给用户之前进行适当排序。
    • 56. 发明授权
    • Personal speech assistant supporting a dialog manager
    • 支持对话管理员的个人演讲助理
    • US06748361B1
    • 2004-06-08
    • US09460077
    • 1999-12-14
    • Liam David ComerfordDavid Carl FrankDavid Nahamoo
    • Liam David ComerfordDavid Carl FrankDavid Nahamoo
    • G10L1522
    • G10L15/28
    • A Personal Speech Assistant (PSA) is a computing apparatus which provides a spoken language interface to another apparatus to which it is attached by supporting execution of a conversational dialog manager and its supporting service engines. In operation, a PSA is connected to a device which provides some service to a user. Any “appliance” is a candidate for enhancement with the PSA. Devices such as, for example, video cassette recorders (VCRs) or Personal Digital Assistants (PDAs), which offer rich, but frequently difficult interfaces, may be made more useful by the integration of a PSA according to the invention. It is a preferred feature of a dialog manager used by the PSA that the user interface properties, in terms of the vocabulary the device understands, the informative prompts it provides, and other aspects of its conversational behavior, are all easily modified to correspond to the preferences or limitations of the user.
    • 个人语音助理(PSA)是一种通过支持会话对话管理器及其支持服务引擎的执行来向附加的另一设备提供口语语言接口的计算设备。 在操作中,PSA连接到向用户提供一些服务的设备。 任何“家电”都是使用PSA进行增强的候选人。 通过集成根据本发明的PSA,可提供诸如例如提供丰富而且经常困难的界面的诸如录像机(VCR)或个人数字助理(PDA)的设备更有用。 PSA使用的对话管理器的优选特征是,用户接口属性(根据设备理解的词汇表),其提供的信息提示以及其会话行为的其他方面都是容易地被修改为对应于 用户的偏好或限制。
    • 58. 发明授权
    • Speech coding via speech recognition and synthesis based on pre-enrolled
phonetic tokens
    • 基于预先录入的语音标记的语音识别和综合语音编码
    • US6119086A
    • 2000-09-12
    • US67863
    • 1998-04-28
    • Abraham IttycheriahStephane H. MaesDavid Nahamoo
    • Abraham IttycheriahStephane H. MaesDavid Nahamoo
    • G10L15/02G10L19/00G10L13/06G10L13/08G10L15/26
    • G10L19/0018
    • A speech coding system, responsive to an input speech signal provided by a system user, comprises: a speech coding portion including a speech recognition system responsive to the input speech signal and having a word vocabulary associated therewith, the speech recognition system recognizing the input speech signal in accordance with the vocabulary and generating phonetic tokens, such as at least one sequence of lefemes, representative of the input speech signal; a channel, responsive to the at least one sequence of lefemes, for transmitting and/or storing the at least one sequence of lefemes; and a speech synthesizing portion, responsive to the transmitted/stored sequence of lefemes, for generating a synthesized speech signal which is representative of the input speech signal provided by the system user using the at least one sequence of lefemes. The speech recognition system preferably generates acoustic parameters from the input speech signal which include voice characteristics of the system user. The speech coding system also preferably comprises a labeler which processes the input speech signal including words uttered by the system user which are not in the word vocabulary associated with the speech recognition system, the labeler generating phonetic tokens, such as at least one sequence of lefemes, optimally representative of the input speech signal. The sequence of lefemes from the labeler and the speech recognition portion are compared, for each speech segment, and the sequence most similar to the input speech is selected for transmission/storage. The speech synthesizing portion of the system preferably performs speech synthesis using pre-enrolled phonetic sub-units or tokens.
    • 响应于由系统用户提供的输入语音信号的语音编码系统包括:语音编码部分,包括响应于输入语音信号并具有与其相关联的词汇词汇的语音识别系统,语音识别系统识别输入语音 信号,并产生语音令牌,例如表示输入语音信号的至少一个左派序列; 响应于所述至少一个左列的序列的信道,用于发送和/或存储所述至少一个左派序列; 以及语音合成部分,响应于所发送/存储的莱佛斯序列,用于产生代表由系统用户使用至少一个左派序列提供的输入语音信号的合成语音信号。 语音识别系统优选地从包括系统用户的语音特征的输入语音信号生成声学参数。 语音编码系统还优选地包括标签器,其处理包括不在与语音识别系统相关联的词汇词汇中的由系统用户发出的单词的输入语音信号,产生语音令牌的标签器,例如至少一个lefemes序列 ,最佳地代表输入语音信号。 对于每个语音段,比较来自标签机和语音识别部分的左派序列,并且选择与输入语音最相似的序列用于传输/存储。 系统的语音合成部分优选地使用预先注册的语音子单元或令牌来执行语音合成。
    • 59. 发明授权
    • Continuous parameter hidden Markov model approach to automatic
handwriting recognition
    • 连续参数隐马尔可夫模型法自动手写识别
    • US5636291A
    • 1997-06-03
    • US467615
    • 1995-06-06
    • Eveline J. BellegardaJerome R. BellegardaDavid NahamooKrishna S. Nathan
    • Eveline J. BellegardaJerome R. BellegardaDavid NahamooKrishna S. Nathan
    • G06K9/62G06K9/68G06K9/70G06K9/00G06F15/00
    • G06K9/6297
    • A computer-based system and method for recognizing handwriting. The present invention includes a pre-processor, a front end, and a modeling component. The present invention operates as follows. First, the present invention identifies the lexemes for all characters of interest. Second, the present invention performs a training phase in order to generate a hidden Markov model for each of the lexemes. Third, the present invention performs a decoding phase to recognize handwritten text. Hidden Markov models for lexemes are produced during the training phase. The present invention performs the decoding phase as follows. The present invention receives test characters to be decoded (that is, to be recognized). The present invention generates sequences of feature vectors for the test characters by mapping in chirographic space. For each of the test characters, the present invention computes probabilities that the test character can be generated by the hidden Markov models. The present invention decodes the test character as the recognized character associated with the hidden Markov model having the greatest probability.
    • 一种用于识别笔迹的基于计算机的系统和方法。 本发明包括预处理器,前端和建模组件。 本发明如下操作。 首先,本发明识别所有感兴趣的人物的词汇。 第二,本发明执行训练阶段,以便为每个词汇生成隐马尔可夫模型。 第三,本发明执行解码阶段来识别手写文本。 训练阶段产生了隐马尔可夫模型。 本发明如下进行解码阶段。 本发明接收要解码的测试字符(即将被识别)。 本发明通过在手写空间中映射来生成用于测试字符的特征向量的序列。 对于每个测试字符,本发明计算由隐马尔可夫模型可以产生测试字符的概率。 本发明将测试字符解码为与具有最大概率的隐马尔可夫模型相关联的识别字符。
    • 60. 发明授权
    • Statistical mixture approach to automatic handwriting recognition
    • 统计混合法自动手写识别
    • US5343537A
    • 1994-08-30
    • US785642
    • 1991-10-31
    • Eveline J. BellegardaJerome R. BellegardaDavid NahamooKrishna S. Nathan
    • Eveline J. BellegardaJerome R. BellegardaDavid NahamooKrishna S. Nathan
    • G06K9/22G06K9/46G06K9/62G06K9/00
    • G06K9/6217G06K9/00416G06K9/00429
    • Method and apparatus for automatic recognition of handwritten text based on a suitable representation of handwriting in one or several feature vector spaces(s), Gaussian modeling in each space, and mixture decoding to take into account the contribution of all relevant prototypes in all spaces. The feature vector space(s) is selected to encompass both a local and a global description of each appropriate point on a pen trajectory. Windowing is performed to capture broad trends in the handwriting, after which a linear transformation is applied to suitably eliminate redundancy. The resulting feature vector space(s) is called chirographic space(s). Gaussian modeling is performed to isolate adequate chirographic prototype distributions in each space, and the mixture coefficients weighting these distributions are trained using a maximum likelihood framework. Decoding can be performed simply and effectively by accumulating the contribution of all relevant prototype distributions. Post-processing using a language model may be included.
    • 基于在一个或多个特征向量空间中的手写的适当表示,每个空间中的高斯建模,以及混合解码,以便考虑所有空间中所有相关原型的贡献,自动识别手写文本的方法和装置。 选择特征向量空间以包含笔轨迹上的每个适当点的局部和全局描述。 执行窗口以捕获手写的广泛趋势,之后应用线性变换以适当地消除冗余。 所得到的特征向量空间称为手绘空间。 执行高斯建模以分离每个空间中的足够的手写原型分布,并且使用最大似然框架训练对这些分布加权的混合系数。 通过积累所有相关原型分布的贡献,可以简单有效地执行解码。 可以包括使用语言模型的后处理。