公开(公告)号：US5995590A

公开(公告)日：1999-11-30

申请号：US35493

申请日：1998-03-05

申请人： Peter Thomas Brunet ,  Abraham P. Ittycheriah ,  Chandrasekhar Narayanaswami ,  Michael Alan Picheny ,  Bhuvana Ramabhadran

发明人： Peter Thomas Brunet ,  Abraham P. Ittycheriah ,  Chandrasekhar Narayanaswami ,  Michael Alan Picheny ,  Bhuvana Ramabhadran

IPC分类号： G10L13/00 ,  H04M1/247 ,  H04M11/00

CPC分类号： H04M1/2475 ,  G10L13/00

摘要： A method and apparatus is disclosed that allows people to carry on unobtrusive phone conversations in business or other settings where it is either not possible or impolite to talk. In the system of FIG. 1, the telephone user one will listen in the same manner as with a regular telephone. However, he will not speak into the telephone microphone. User one instead employs a unit including a keyboard to enter the text corresponding to what he wants to say. The text is converted into a synthesized speech using TTS apparatus and a voice output is sent to the microphone of the phone apparatus. The telephone apparatus transmits the synthesized voice signal over a standard telephone line to a unit including a conventional telephone speaker 26 and telephone microphone. User two, the party using the telephone at the other end, listens to a synthesized voice, but user one listens to the actual voice of user two with the telephone speaker, unless user two is also using a system similar to that of user one. Handwritten text may also be used in the system by employing a computer with a character recognition program as an input. In such a case handwriting is converted into synthesized sound and inputted into the telephone microphone. The telephone system can be used by the hearing impaired without involving a third party human transcriber.

摘要翻译： 公开了一种方法和装置，其允许人们在不可能或不礼貌地谈论的商业或其他设置中进行不引人注意的电话对话。 在图1的系统中 1，电话用户将以与普通电话相同的方式收听。 不过，他不会和电话麦克风说话。 用户1使用包括键盘的单元来输入与他想说的对应的文本。 使用TTS装置将文本转换成合成语音，并且将语音输出发送到电话装置的麦克风。 电话设备通过标准电话线将合成语音信号发送到包括常规电话扬声器26和电话麦克风的单元。 用户二，在另一端使用电话的一方侦听合成语音，但用户一听电话扬声器听用户二的实际语音，除非用户二也使用类似于用户二的系统。 通过采用具有字符识别程序的计算机作为输入，也可以在系统中使用手写文本。 在这种情况下，笔迹被转换成合成声音并被输入到电话麦克风。 电话系统可以由听力障碍者使用，而不涉及第三方人类录音机。

公开(公告)号：US5680509A

公开(公告)日：1997-10-21

申请号：US312584

申请日：1994-09-27

申请人： Ponani S. Gopalakrishnan ,  David Nahamoo ,  Mukund Padmanabhan ,  Michael Alan Picheny

发明人： Ponani S. Gopalakrishnan ,  David Nahamoo ,  Mukund Padmanabhan ,  Michael Alan Picheny

IPC分类号： G10L15/06 ,  G10L15/08 ,  G10L5/06

CPC分类号： G10L15/063 ,  G10L15/08

摘要： A method and apparatus for estimating the probability of phones, a-posteriori, in the context of not only the acoustic feature at that time, but also the acoustic features in the vicinity of the current time, and its use in cutting down the search-space in a speech recognition system. The method constructs and uses a decision tree, with the predictors of the decision tree being the vector-quantized acoustic feature vectors at the current time, and in the vicinity of the current time. The process starts with an enumeration of all (predictor, class) events in the training data at the root node, and successively partitions the data at a node according to the most informative split at that node. An iterative algorithm is used to design the binary partitioning. After the construction of the tree is completed, the probability distribution of the predicted class is stored at all of its terminal leaves. The decision tree is used during the decoding process by tracing a path down to one of its leaves, based on the answers to binary questions about the vector-quantized acoustic feature vector at the current time and its vicinity.

摘要翻译： 在不仅在当时的声学特征以及当前时间附近的声学特征的上下文中估计电话的概率的方法和装置，以及其用于减少搜索 - 语音识别系统中的空间。 该方法构造并使用决策树，其中决策树的预测变量是当前时间和当前时间附近的矢量量化的声学特征向量。 该过程从在根节点的训练数据中的所有（预测器，类）事件的枚举开始，并且根据该节点处的最多信息拆分在节点处依次划分数据。 迭代算法用于设计二进制分区。 树完成后，预测类的概率分布存储在其所有终端叶上。 基于对当前时间及其附近的向量量化声学特征向量的二进制问题的答案，在解码过程中使用决策树通过跟踪到其叶子之一的路径。

公开(公告)号：US08145491B2

公开(公告)日：2012-03-27

申请号：US10208453

申请日：2002-07-30

申请人： Wael Mohamed Hamza ,  Michael Alan Picheny

发明人： Wael Mohamed Hamza ,  Michael Alan Picheny

IPC分类号： G10L13/06

CPC分类号： G10L13/07

摘要： When pitch of a speech segment is being modified from a current pitch to a requested pitch, and the difference between these is relatively large, a pitch modification algorithm is used to modify the pitch of the speech segment. When the difference between current and requested pitches is relatively small, the pitch of the speech segment is not modified. After one or the other speech modification techniques are used, then the resultant modified speech segment is overlapped and added to previously modified speech segments. A modification ratio is determined in order to quantify the difference between the current and requested pitches for a speech segment. The modification ratio is a ratio between the requested and current pitches. Low and high ratio thresholds are used to determine when pitch is being modified to a predetermined high degree, and whether pitch of the speech segment will or will not be modified.

摘要翻译： 当语音片段的节距从当前音调修改为所请求的节距，并且它们之间的差异相对较大时，使用音调修改算法来修改语音片段的音高。 当电流和请求间距之差相对较小时，语音段的音调不被修改。 在使用一种或另一种语音修改技术之后，将所得到的修改语音段重叠并添加到先前修改的语音段。 确定修正率以量化语音段的当前和所请求的间距之间的差异。 修正比是要求和当前间距之间的比率。 使用低和高比率阈值来确定音调何时被修改到预定的高度，以及语音片段的音调是否将被修改。

公开(公告)号：US07464031B2

公开(公告)日：2008-12-09

申请号：US10724536

申请日：2003-11-28

申请人： Scott E. Axelrod ,  Sreeram Viswanath Balakrishnan ,  Stanley F. Chen ,  Yuging Gao ,  Ramesh A. Gopinath ,  Hong-Kwang Kuo ,  Benoit Maison ,  David Nahamoo ,  Michael Alan Picheny ,  George A. Saon ,  Geoffrey G. Zweig

发明人： Scott E. Axelrod ,  Sreeram Viswanath Balakrishnan ,  Stanley F. Chen ,  Yuging Gao ,  Ramesh A. Gopinath ,  Hong-Kwang Kuo ,  Benoit Maison ,  David Nahamoo ,  Michael Alan Picheny ,  George A. Saon ,  Geoffrey G. Zweig

IPC分类号： G10L15/00 ,  G10L15/20

CPC分类号： G10L15/063 ,  G10L15/02 ,  G10L15/14 ,  G10L2015/085

摘要： In a speech recognition system, the combination of a log-linear model with a multitude of speech features is provided to recognize unknown speech utterances. The speech recognition system models the posterior probability of linguistic units relevant to speech recognition using a log-linear model. The posterior model captures the probability of the linguistic unit given the observed speech features and the parameters of the posterior model. The posterior model may be determined using the probability of the word sequence hypotheses given a multitude of speech features. Log-linear models are used with features derived from sparse or incomplete data. The speech features that are utilized may include asynchronous, overlapping, and statistically non-independent speech features. Not all features used in training need to appear in testing/recognition.

摘要翻译： 在语音识别系统中，提供了具有多个语音特征的对数线性模型的组合来识别未知语音语音。 语音识别系统使用对数线性模型对与语音识别相关的语言单位的后验概率进行建模。 后验模型捕获了语言单位给出观察到的语音特征和后验模型参数的概率。 可以使用给定多个语音特征的单词序列假设的概率来确定后验模型。 对数线性模型与来自稀疏或不完整数据的特征一起使用。 所使用的语音特征可以包括异步，重叠和统计上非独立的语音特征。 培训中使用的并非所有功能都需要出现在测试/识别中。

公开(公告)号：US06073096A

公开(公告)日：2000-06-06

申请号：US18350

申请日：1998-02-04

申请人： Yuqing Gao ,  Mukund Padmanabhan ,  Michael Alan Picheny

发明人： Yuqing Gao ,  Mukund Padmanabhan ,  Michael Alan Picheny

IPC分类号： G10L15/07 ,  G10L15/06

CPC分类号： G10L15/07

摘要： A method of speech recognition, in accordance with the present invention includes the steps of grouping acoustics to form classes based on acoustic features, clustering training speakers by the classes to provide class-specific cluster systems, selecting from the cluster systems, a subset of cluster systems closest to adaptation data from a test speaker, transforming the subset of cluster systems to bring the subset of cluster systems closer to the test speaker based on the adaptation data to form adapted cluster systems and combining the adapted cluster systems to create a speaker adapted system for decoding speech from the test speaker. System and methods for building speech recognition systems as well as adapting speaker systems for class-specific speaker clusters are included.

摘要翻译： 根据本发明的语音识别方法包括以下步骤：基于声学特征对声学进行分组以形成类别，由类别聚类训练讲话者以提供特定类别的集群系统，从集群系统中选择集群的子集 最接近来自测试说话者的自适应数据的系统，基于适配数据来改变集群系统的子集以使集群系统的子集更靠近测试说话者，以形成适应的集群系统，并组合适应的集群系统以创建一个说话者适配系统 用于解码来自测试扬声器的语音。 包括构建语音识别系统的系统和方法以及适用于类特定扬声器群的扬声器系统。

公开(公告)号：US5806021A

公开(公告)日：1998-09-08

申请号：US700823

申请日：1996-09-04

申请人： Chengjun Julian Chen ,  Fu-Hua Liu ,  Michael Alan Picheny

发明人： Chengjun Julian Chen ,  Fu-Hua Liu ,  Michael Alan Picheny

IPC分类号： G06F17/27 ,  G06F17/20

CPC分类号： G06F17/277

摘要： An automatic segmenter for continuous text segments such text in a rapid, consistent and semantically accurate manner. Two statistical methods for segmentation of continuous text are used. The first method, called "forward-backward matching", is easy and fast but can produce occasional errors in long phrases. The second method, called "statistical stack search segmenter", utilizes statistical language models to generate more accurate segmentation output at an expense of two times more execution time than the "forward-backward matching" method. In some applications where speed is a major concern, "forward-backward matching" can be used, while in other applications where highly accurate output is desired, "statistical stack search segmenter" is ideal.

摘要翻译： 用于以快速，一致和语义准确的方式连续文本段的自动分段器。 使用两种连续文本分割的统计方法。 第一种称为“前向 - 后向匹配”的方法是简单快捷的，但可能会产生长时间的误差。 称为“统计堆栈搜索分段器”的第二种方法利用统计语言模型以比“前向 - 后向匹配”方法多两倍的执行时间来生成更精确的分段输出。 在速度是主要关注的一些应用中，可以使用“前向后匹配”，而在需要高精度输出的其他应用中，“统计栈搜索分段器”是理想的。

公开(公告)号：US07490042B2

公开(公告)日：2009-02-10

申请号：US11092057

申请日：2005-03-29

申请人： Ellen Marie Eide ,  Wael Mohamed Hamza ,  Michael Alan Picheny

发明人： Ellen Marie Eide ,  Wael Mohamed Hamza ,  Michael Alan Picheny

IPC分类号： G10L15/00

CPC分类号： G10L13/027 ,  G10L15/22

摘要： A technique for producing speech output in an automatic dialog system in accordance with a detected context is provided. Communication is received from a user at the automatic dialog system. A context of the communication from the user is detected in a context detector of the automatic dialog system. A message is created in a natural language generator of the automatic dialog system in communication with the context detector. The message is conveyed to the user through a speech synthesis system of the automatic dialog system, in communication with the natural language generator and the context detector. Responsive to a detected level of ambient noise, the context detector provides at least one command in a markup language to cause the natural language generator to create the message using maximally intelligible words and to cause the speech synthesis system to convey the message with increased volume and decreased speed.

摘要翻译： 提供了一种根据检测到的上下文在自动对话系统中产生语音输出的技术。 在自动对话系统中从用户接收通信。 在自动对话系统的上下文检测器中检测来自用户的通信的上下文。 在与上下文检测器通信的自动对话系统的自然语言生成器中创建消息。 该消息通过与自然语言生成器和上下文检测器通信的自动对话系统的语音合成系统传送给用户。 响应于检测到的环境噪声水平，上下文检测器以标记语言提供至少一个命令，以使自然语言生成器使用最大可理解的单词来创建消息，并且使得语音合成系统以增加的音量传达消息，并且 降低速度

公开(公告)号：US20080221874A1

公开(公告)日：2008-09-11

申请号：US12123778

申请日：2008-05-20

申请人： Yuging Cao ,  Michael Alan Picheny ,  Ruhi Sarikaya

发明人： Yuging Cao ,  Michael Alan Picheny ,  Ruhi Sarikaya

IPC分类号： G06F17/27

CPC分类号： G06F17/271 ,  G06F17/2755

摘要： A method, apparatus and computer instructions is provided for fast semi-automatic semantic annotation. Given a limited annotated corpus, the present invention assigns a tag and a label to each word of the next limited annotated corpus using a parser engine, a similarity engine, and a SVM engine. A rover then combines the parse trees from the three engines and annotates the next chunk of limited annotated corpus with confidence, such that the efforts required for human annotation is reduced.

摘要翻译： 提供了一种用于快速半自动语义注释的方法，装置和计算机指令。 给定有限的注释语料库，本发明使用解析器引擎，相似性引擎和SVM引擎向下一个有限注释语料库的每个单词分配标签和标签。 然后，流动站组合来自三个引擎的解析树，并自信地注释下一批有限注释语料库，从而减少人体注释所需的努力。

公开(公告)号：US6023673A

公开(公告)日：2000-02-08

申请号：US869061

申请日：1997-06-04

申请人： Raimo Bakis ,  David Nahamoo ,  Michael Alan Picheny ,  Jan Sedivy

发明人： Raimo Bakis ,  David Nahamoo ,  Michael Alan Picheny ,  Jan Sedivy

IPC分类号： G10L5/06 ,  G10L9/00

CPC分类号： G10L15/083

摘要： A speech coding apparatus and method uses a hierarchy of prototype sets to code an utterance while consuming fewer computing resources. The value of at least one feature of an utterance is measured during each of a series of successive time intervals to produce a series of feature vector signals representing the feature values. A plurality of level subsets of prototype vector signals is computed, wherein each prototype vector signal in a higher level subset is associated with at least one prototype vector signal in a lower level subset. Each level subset contains a plurality of prototype vector signals, with lower level subsets containing more prototypes than higher level subsets. The closeness of the feature value of the first feature vector signal is compared to the parameter values of prototype vector signals in the first level subset of prototype vector signals to obtain a ranked list of prototype match scores for the first feature vector signal and each prototype vector signal in the first level subset. The closeness of the feature value of the first feature vector signal is compared to the parameter values of each prototype vector signal in a second (lower) level subset that is associated with the highest ranking prototype vectors in the first level subset, to obtain a second ranked list of prototype match scores. The identification value of the prototype vector signal in the second ranked list having the best prototype match score is output as a coded utterance representation signal of the first feature vector signal.

摘要翻译： 语音编码装置和方法使用原型集的层次来编码话语，同时消耗更少的计算资源。 在一系列连续时间间隔的每一个期间测量话音的至少一个特征的值，以产生表示特征值的一系列特征向量信号。 计算原型矢量信号的多个级别子集，其中较高级子集中的每个原型矢量信号与较低级子集中的至少一个原型矢量信号相关联。 每个级别子集包含多个原型矢量信号，其中较低级子集包含比较高级子集更多的原型。 将第一特征向量信号的特征值的接近度与原型矢量信号的第一级子集中的原型矢量信号的参数值进行比较，以获得第一特征向量信号和每个原型矢量的原型匹配分数的排序列表 信号在第一级子集。 将第一特征向量信号的特征值的接近度与与第一级子集中的最高排序原型向量相关联的第二（较低）级子集中的每个原型矢量信号的参数值进行比较，以获得第二 排名榜的原型比赛得分。 将具有最佳原型匹配分数的第二等级列表中的原型矢量信号的识别值输出为第一特征向量信号的编码话音表示信号。

公开(公告)号：US07610191B2

公开(公告)日：2009-10-27

申请号：US10959523

申请日：2004-10-06

申请人： Yuqing Gao ,  Michael Alan Picheny ,  Ruhi Sarikaya

发明人： Yuqing Gao ,  Michael Alan Picheny ,  Ruhi Sarikaya

IPC分类号： G06F17/27

CPC分类号： G06F17/271 ,  G06F17/2755

摘要： A method, apparatus and computer instructions is provided for fast semi-automatic semantic annotation. Given a limited annotated corpus, the present invention assigns a tag and a label to each word of the next limited annotated corpus using a parser engine, a similarity engine, and a SVM engine. A rover then combines the parse trees from the three engines and annotates the next chunk of limited annotated corpus with confidence, such that the efforts required for human annotation is reduced.

摘要翻译： 提供了一种用于快速半自动语义注释的方法，装置和计算机指令。 给定有限的注释语料库，本发明使用解析器引擎，相似性引擎和SVM引擎为下一个有限注释语料库的每个单词分配标签和标签。 然后，流动站组合来自三个引擎的解析树，并自信地注释下一批有限注释语料库，从而减少人体注释所需的努力。