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公开(公告)号：US07562017B1
公开(公告)日：2009-07-14
申请号：US11862656
申请日：2007-09-27
申请人： Dilek Z. Hakkani-Tur , Mazin G. Rahim , Gokhan Tur
发明人： Dilek Z. Hakkani-Tur , Mazin G. Rahim , Gokhan Tur
CPC分类号： G10L15/1822
摘要： An active labeling process is provided that aims to minimize the number of utterances to be checked again by automatically selecting the ones that are likely to be erroneous or inconsistent with the previously labeled examples. In one embodiment, the errors and inconsistencies are identified based on the confidences obtained from a previously trained classifier model. In a second embodiment, the errors and inconsistencies are identified based on an unsupervised learning process. In both embodiments, the active labeling process is not dependent upon the particular classifier model.
摘要翻译： 提供了一种主动标注过程，其目的是通过自动选择可能是错误的或与先前标记的示例不一致的那些来最小化要再次检查的话语的数量。 在一个实施例中，基于从先前训练的分类器模型获得的信心来识别误差和不一致性。 在第二实施例中，基于无监督的学习过程来识别错误和不一致。 在两个实施方案中，活性标记过程不依赖于特定的分类器模型。
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公开(公告)号：US07496503B1
公开(公告)日：2009-02-24
申请号：US11611983
申请日：2006-12-18
申请人： Richard Vandervoort Cox , Stephen Michael Marcus , Mazin G. Rahim , Nambirajan Seshadri , Robert Douglas Sharp
发明人： Richard Vandervoort Cox , Stephen Michael Marcus , Mazin G. Rahim , Nambirajan Seshadri , Robert Douglas Sharp
IPC分类号： G10L19/00
摘要： Recognizing a stream of speech received as speech vectors over a lossy communications link includes constructing for a speech recognizer a series of speech vectors from packets received over a lossy packetized transmission link, wherein some of the packets associated with each speech vector are lost or corrupted during transmission. Each constructed speech vector is multi-dimensional and includes associated features. After waiting for a predetermined time, speech vectors are generated and potentially corrupted features within the speech vector are indicated to the speech recognizer when present. Speech recognition is attempted at the speech recognizer on the speech vectors when corrupted features are present. This recognition may be based only on certain or valid features within each speech vector. Retransmission of a missing or corrupted packet is requested when corrupted values are indicated by the indicating step and when the attempted recognition step fails.
摘要翻译： 识别通过有损通信链路作为语音向量接收的语音流包括：通过有损分组化传输链路从分组接收的分组来构建语音识别器的一系列语音向量，其中与每个语音向量相关联的一些分组丢失或损坏 传输。 每个构造的语音向量是多维的并且包括相关联的特征。 在等待预定的时间之后，产生语音向量，并且在存在时将语音向量内潜在的损坏的特征指示给语音识别器。 当存在损坏的特征时，语音识别器在语音向量上尝试语音识别。 该识别可以仅基于每个语音向量内的某些或有效特征。 当指示步骤指示损坏的值以及尝试的识别步骤失败时，请求重新发送丢失或损坏的数据包。
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63.发明授权公开(公告)号：US07451089B1
公开(公告)日：2008-11-11
申请号：US11675166
申请日：2007-02-15
摘要： A voice-enabled help desk service is disclosed. The service comprises an automatic speech recognition module for recognizing speech from a user, a spoken language understanding module for understanding the output from the automatic speech recognition module, a dialog management module for generating a response to speech from the user, a natural voices text-to-speech synthesis module for synthesizing speech to generate the response to the user, and a frequently asked questions module. The frequently asked questions module handles frequently asked questions from the user by changing voices and providing predetermined prompts to answer the frequently asked question.
摘要翻译： 公开了支持语音的帮助台服务。 该服务包括用于识别来自用户的语音的自动语音识别模块，用于理解来自自动语音识别模块的输出的口语语言理解模块，用于生成来自用户对语音的响应的对话管理模块，自然语音文本 - 语音合成模块，用于合成语音以产生对用户的响应，以及常见问题模块。 常见问题模块通过改变语音来处理用户的常见问题，并提供预定的提示来回答常见问题。
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公开(公告)号：US20080270130A1
公开(公告)日：2008-10-30
申请号：US12165755
申请日：2008-07-01
申请人： Tirso M. Alonso , Ilana Bromberg , Dilek Z. Hakkani-Tur , Barbara B. Hollister , Mazin G. Rahim , Giuseppe Riccardi , Lawrence Lyon Rose , Daniel Leon Stern , Gokhan Tur , James M. Wilson
发明人： Tirso M. Alonso , Ilana Bromberg , Dilek Z. Hakkani-Tur , Barbara B. Hollister , Mazin G. Rahim , Giuseppe Riccardi , Lawrence Lyon Rose , Daniel Leon Stern , Gokhan Tur , James M. Wilson
IPC分类号： G10L15/00
CPC分类号： G10L15/19 , G10L15/063 , G10L15/183 , H04M3/4936
摘要： Systems and methods for annotating speech data. The present invention reduces the time required to annotate speech data by selecting utterances for annotation that will be of greatest benefit. A selection module uses speech models, including speech recognition models and spoken language understanding models, to identify utterances that should be annotated based on criteria such as confidence scores generated by the models. These utterances are placed in an annotation list along with a type of annotation to be performed for the utterances and an order in which the annotation should proceed. The utterances in the annotation list can be annotated for speech recognition purposes, spoken language understanding purposes, labeling purposes, etc. The selection module can also select utterances for annotation based on previously annotated speech data and deficiencies in the various models.
摘要翻译： 用于注释语音数据的系统和方法。 本发明通过选择最有益的用于注释的话语来减少注释语音数据所需的时间。 选择模块使用包括语音识别模型和语言理解模型在内的语音模型来基于诸如由模型产生的置信度得分的标准来识别应当注释的话语。 这些话语被放置在注释列表中，以及要为语句执行的注释类型以及注释应该继续执行的顺序。 注释列表中的话语可以被注释用于语音识别目的，语言理解目的，标签目的等。选择模块还可以基于先前注释的语音数据和各种模型中的缺陷来选择用于注释的话语。
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65.发明授权公开(公告)号：US07328146B1
公开(公告)日：2008-02-05
申请号：US11484120
申请日：2006-07-11
申请人： Hiyan Alshawi , Giuseppe DiFabrizzio , Narendra K. Gupta , Mazin G. Rahim , Robert E. Schapire , Yoram Singer
发明人： Hiyan Alshawi , Giuseppe DiFabrizzio , Narendra K. Gupta , Mazin G. Rahim , Robert E. Schapire , Yoram Singer
IPC分类号： G06F17/20
CPC分类号： G06F17/28
摘要： A system for understanding entries, such as speech, develops a classifier by employing prior knowledge with which a given corpus of training entries is enlarged threefold. A rule is created for each of the labels employed in the classifier, and the created rules are applied to the given corpus to create a corpus of attachments by appending a weight of ηp(x), or 1−ηp(x), to labels of entries that meet, or fail to meet, respectively, conditions of the labels' rules, and to also create a corpus of non-attachments by appending a weight of 1−ηp(x), or ηp(x), to labels of entries that meet, or fail to meet conditions of the labels' rules.
摘要翻译： 用于理解诸如言语之类的条目的系统通过采用将给定的训练条目语料库放大三倍的先验知识来开发分类器。 为分类器中使用的每个标签创建规则，并将创建的规则应用于给定的语料库，以通过将一个权重为etap（x）或1-etap（x）附加到标签来创建附件语料库 分别符合或未能满足标签规则的条件的条目，并通过将1-etap（x）或etap（x）的权重附加到标签的标签上来创建非附件语料库 满足或不符合标签规则条件的条目。
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公开(公告)号：US07181399B1
公开(公告)日：2007-02-20
申请号：US09314637
申请日：1999-05-19
申请人： Mazin G. Rahim , Giuseppe Riccardi , Jeremy Huntley Wright , Bruce Melvin Buntschuh , Allen Louis Gorin
发明人： Mazin G. Rahim , Giuseppe Riccardi , Jeremy Huntley Wright , Bruce Melvin Buntschuh , Allen Louis Gorin
CPC分类号： G10L15/142
摘要： A system for recognizing connected digits in natural spoken dialogue includes a speech recognition processor that receives unconstrained fluent input speech and produces a string of words that can include a numeric language, and a numeric understanding processor that converts the string of words into a sequence of digits based on a set of rules. An acoustic model database utilized by the speech recognition processor includes a first set of hidden Markov models that characterize the acoustic features of numeric words and phrases, a second set of hidden Markov models that characterize the acoustic features of the remaining vocabulary words, and a filler model that characterizes the acoustic features of out-of-vocabulary utterances. An utterance verification processor verifies the accuracy of the string of words. A validation database stores a grammar, and a string validation processor outputs validity information based on a comparison of the sequence of digits with the grammar. A dialogue manager processor initiates an action based on the validity information.
摘要翻译： 用于识别自然语言对话中的连接数字的系统包括语音识别处理器，其接收无约束的流畅输入语音并产生可包括数字语言的单词串，以及将该字符串转换为数字序列的数字理解处理器 基于一套规则。 由语音识别处理器使用的声学模型数据库包括表征数字单词和短语的声学特征的第一组隐马尔可夫模型，表征剩余词汇单词的声学特征的第二组隐马尔可夫模型，以及填充 表征了词汇外语音的声学特征的模型。 话语验证处理器验证字串的准确性。 验证数据库存储语法，并且字符串验证处理器基于数字序列与语法的比较来输出有效性信息。 对话管理器处理器基于有效性信息启动动作。
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公开(公告)号：US07171359B1
公开(公告)日：2007-01-30
申请号：US10902304
申请日：2004-07-29
申请人： Richard Vandervoort Cox , Stephen Michael Marcus , Mazin G. Rahim , Nambirajan Seshadri , Robert Douglas Sharp
发明人： Richard Vandervoort Cox , Stephen Michael Marcus , Mazin G. Rahim , Nambirajan Seshadri , Robert Douglas Sharp
IPC分类号： G10L15/06
摘要： Recognizing a stream of speech received as speech vectors over a lossy communications link includes constructing for a speech recognizer a series of speech vectors from packets received over a lossy packetized transmission link, wherein some of the packets associated with each speech vector are lost or corrupted during transmission. Each constructed speech vector is multi-dimensional and includes associated features. Potentially corrupted features within the speech vector are indicated to the speech recognizer when present. Speech recognition is attempted at the speech recognizer on the speech vectors when corrupted features are present. This recognition may be based only on certain or valid features within each speech vector. Retransmission of a missing or corrupted packet is requested when corrupted values are indicated by the indicating step and when the attempted recognition step fails.
摘要翻译： 识别通过有损通信链路作为语音向量接收的语音流包括：通过有损分组化传输链路从分组接收的分组来构建语音识别器的一系列语音向量，其中与每个语音向量相关联的一些分组丢失或损坏 传输。 每个构造的语音向量是多维的并且包括相关联的特征。 语音向量中的潜在损坏的特征在存在时被指示给语音识别器。 当存在损坏的特征时，语音识别器在语音向量上尝试语音识别。 该识别可以仅基于每个语音向量内的某些或有效特征。 当指示步骤指示损坏的值以及尝试的识别步骤失败时，请求重新发送丢失或损坏的数据包。
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公开(公告)号：US5806022A
公开(公告)日：1998-09-08
申请号：US575378
申请日：1995-12-20
申请人： Mazin G. Rahim , Jay Gordon Wilpon
发明人： Mazin G. Rahim , Jay Gordon Wilpon
IPC分类号： G10L15/20 , G10L11/00 , G10L15/02 , G10L15/08 , G10L15/10 , G10L21/02 , G10L3/02 , G10L9/00 , H04M1/76
摘要： Speech recognition processing is compensated for improving robustness of speech recognition in the presence of enhanced speech signals. The compensation overcomes the adverse effects that speech signal enhancement may have on speech recognition performance, where speech signal enhancement causes acoustical mismatches between recognition models trained using unenhanced speech signals and feature data extracted from enhanced speech signals. Compensation is provided at the front end of an automatic speech recognition system by combining linear predictive coding and mel-based cepstral parameter analysis for computing cepstral features of transmitted speech signals used for speech recognition processing by selectively weighting mel-filter banks when processing frequency domain representations of the enhanced speech signals.
摘要翻译： 在增强语音信号的存在下，语音识别处理被补偿以提高语音识别的鲁棒性。 补偿克服语音信号增强可能对语音识别性能的不利影响，其中语音信号增强导致使用未增强语音信号训练的识别模型和从增强语音信号提取的特征数据之间的声学失配。 在自动语音识别系统的前端通过组合线性预测编码和基于梅尔的倒谱参数分析来提供用于计算用于语音识别处理的传输语音信号的倒谱特征的补偿，其中当处理频域表示时，通过选择性地加权梅尔滤波器组 的增强语音信号。
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公开(公告)号：US5737489A
公开(公告)日：1998-04-07
申请号：US528902
申请日：1995-09-15
申请人： Wu Chou , Biing-Hwang Juang , Chin-Hui Lee , Mazin G. Rahim
发明人： Wu Chou , Biing-Hwang Juang , Chin-Hui Lee , Mazin G. Rahim
CPC分类号： G10L15/144 , G10L15/063 , G10L15/10
摘要： In a speech recognition system, a recognition processor receives an unknown utterance signal as input. The recognition processor in response to the unknown utterance signal input accesses a recognition database and scores the utterance signal against recognition models in the recognition database to classify the unknown utterance and to generate a hypothesis speech signal. A verification processor receives the hypothesis speech signal as input to be verified. The verification processor accesses a verification database to test the hypothesis speech signal against verification models reflecting a preselected type of training stored in the verification database. Based on the verification test, the verification processor generates a confidence measure signal. The confidence measure signal can be compared against a verification threshold to determine the accuracy of the recognition decision made by the recognition processor.
摘要翻译： 在语音识别系统中，识别处理器接收未知的话音信号作为输入。 响应于未知话语信号输入的识别处理器访问识别数据库，并根据识别数据库中的识别模型对话音信号进行评分，以对未知话语进行分类并生成假设语音信号。 验证处理器接收假设语音信号作为待验证的输入。 验证处理器访问验证数据库以针对反映存储在验证数据库中的预选类型的训练的验证模型来测试假设语音信号。 基于验证测试，验证处理器产生置信度测量信号。 可以将置信度信号与验证阈值进行比较，以确定由识别处理器进行的识别决策的准确性。
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