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1. 发明授权

US06219638B1 Telephone messaging and editing system 有权
标题翻译：电话信息和编辑系统
公开(公告)号：US06219638B1
公开(公告)日：2001-04-17
申请号：US09185332
申请日：1998-11-03
申请人： Mukund Padmanabhan , Michael Picheny , David Nahamoo , Salim Roukos
发明人： Mukund Padmanabhan , Michael Picheny , David Nahamoo , Salim Roukos
IPC分类号： G10L1508
CPC分类号： H04M3/53366 , G10L15/22 , G10L2015/221 , H04M3/5307 , H04M2201/40 , H04M2201/60
摘要： A messaging system for receiving speech over a telephone and converting the speech to text includes a first server for receiving speech input by a user, a speech recognition system for converting the speech to text, a speech synthesizer for converting the text to speech for playing back the synthesized speech for correction by the user and a correction mechanism for enabling the user to correct the speech such that the corrected speech is provided as text for transmittal over a communication system.
摘要翻译：一种用于通过电话接收语音并将语音转换为文本的消息系统包括用于接收用户输入的语音的第一服务器，用于将语音转换为文本的语音识别系统，用于将文本转换为语音以进行回放的语音合成器用于用户校正的合成语音和用于使用户能够校正语音的校正机制，使得校正的语音被提供为用于通过通信系统传送的文本。

2. 发明授权

US5787394A State-dependent speaker clustering for speaker adaptation 失效
标题翻译：用于说话者适应的状态依赖的扬声器聚类
公开(公告)号：US5787394A
公开(公告)日：1998-07-28
申请号：US572223
申请日：1995-12-13
申请人： Lalit Rai Bahl , Ponani Gopalakrishnan , David Nahamoo , Mukund Padmanabhan
发明人： Lalit Rai Bahl , Ponani Gopalakrishnan , David Nahamoo , Mukund Padmanabhan
IPC分类号： G10L15/06 , G10L5/06
CPC分类号： G10L15/07 , G10L2015/0631
摘要： A system and method for adaptation of a speaker independent speech recognition system for use by a particular user. The system and method gather acoustic characterization data from a test speaker and compare the data with acoustic characterization data generated for a plurality of training speakers. A match score is computed between the test speaker's acoustic characterization for a particular acoustic subspace and each training speaker's acoustic characterization for the same acoustic subspace. The training speakers are ranked for the subspace according to their scores and a new acoustic model is generated for the test speaker based upon the test speaker's acoustic characterization data and the acoustic characterization data of the closest matching training speakers. The process is repeated for each acoustic subspace.
摘要翻译：一种适用于特定用户使用的独立于说话者的语音识别系统的系统和方法。该系统和方法从测试扬声器收集声学表征数据，并将数据与为多个训练说话者生成的声学特征数据进行比较。在特定声学子空间的测试扬声器的声学特性与相同声学子空间的每个训练说话者的声学特性之间计算匹配分数。训练演讲者根据其分数对子空间进行排名，并且基于测试讲者的声学表征数据和最接近的匹配训练说话者的声学表征数据为测试说话者生成新的声学模型。对于每个声学子空间重复该过程。

3. 发明授权

US6058205A System and method for partitioning the feature space of a classifier in a pattern classification system 失效
公开(公告)号：US6058205A
公开(公告)日：2000-05-02
申请号：US781574
申请日：1997-01-09
申请人： Lalit Rai Bahl , Peter Vincent deSouza , David Nahamoo , Mukund Padmanabhan
发明人： Lalit Rai Bahl , Peter Vincent deSouza , David Nahamoo , Mukund Padmanabhan
IPC分类号： G06K9/62 , G06F17/20
CPC分类号： G06K9/6282
摘要： A system and method are provided which partition the feature space of a classifier by using hyperplanes to construct a binary decision tree or hierarchical data structure for obtaining the class probabilities for a particular feature vector. One objective in the construction of the decision tree is to minimize the average entropy of the empirical class distributions at each successive node or subset, such that the average entropy of the class distributions at the terminal nodes is minimized. First, a linear discriminant vector is computed that maximally separates the classes at any particular node. A threshold is then chosen that can be applied on the value of the projection onto the hyperplane such that all feature vectors that have a projection onto the hyperplane that is less than the threshold are assigned to a child node (say, left child node) and the feature vectors that have a projection greater than or equal to the threshold are assigned to a right child node. The above two steps are then repeated for each child node until the data at a node falls below a predetermined threshold and the node is classified as a terminal node (leaf of the decision tree). After all non-terminal nodes have been processed, the final step is to store a class distribution associated with each terminal node. The class probabilities for a particular feature vector can then be obtained by traversing the decision tree in a top-down fashion until a terminal node is identified which corresponds to the particular feature vector. The information provided by the decision tree is that, in computing the class probabilities for the particular feature vector, only the small number of classes associated with that particular terminal node need be considered. Alternatively, the required class probabilities can be obtained simply by taking the stored distribution of the terminal node associated with the particular feature vector.

4. 发明授权

US5680509A Method and apparatus for estimating phone class probabilities a-posteriori using a decision tree 失效
标题翻译：用于使用决策树估计电话类概率的方法和装置
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。

5. 发明授权

US5729656A Reduction of search space in speech recognition using phone boundaries and phone ranking 失效
标题翻译：使用手机边界和手机排名减少语音识别中的搜索空间
公开(公告)号：US5729656A
公开(公告)日：1998-03-17
申请号：US347013
申请日：1994-11-30
申请人： David Nahamoo , Mukund Padmanabhan
发明人： David Nahamoo , Mukund Padmanabhan
IPC分类号： G10L15/00 , G10L15/02 , G10L15/04 , G10L15/14 , G10L5/06
CPC分类号： G10L15/04 , G10L15/142 , G10L2015/085
摘要： A method for estimating the probability of phone boundaries and the accuracy of the acoustic modelling in reducing a search-space in a speech recognition system. The accuracy of the acoustic modelling is quantified by the rank of the correct phone. The system includes a microphone for converting an utterance into an electrical signal, which is processed by an acoustic processor and label match which finds the best-matched acoustic label prototype. A probability distribution on phone boundaries is produced for every time frame using a first decision tree. These probabilities are compared to a threshold and some time frames are identified as boundaries between phones. An acoustic score is computed for all phones between every given pair of hypothesized boundaries, and the phones are ranked on the basis of this score. A second decision tree is traversed for every time frame to obtain the worst case rank of the correct phone at that time, and a short list of allowed phones is made for every time frame. A fast acoustic word match processor matches the label string from the acoustic processor to produce an utterance signal which includes at least one word. From recognition candidates produced by the fast acoustic match and the language model, the detailed acoustic match matches the label string from the acoustic processor against acoustic word models and outputs a word string corresponding to an utterance.
摘要翻译：一种用于在减少语音识别系统中的搜索空间中估计电话边界的概率和声学建模的准确度的方法。声学建模的准确度由正确的手机的等级来量化。该系统包括用于将发音转换成电信号的麦克风，该电信号由声学处理器处理，并且标签匹配找到最佳匹配的声学标签原型。使用第一决策树为每个时间帧产生电话边界上的概率分布。将这些概率与阈值进行比较，并且将一些时间帧识别为电话之间的边界。对于所有给定的一对假设边界之间的所有电话，计算声学得分，并且手机基于该分数进行排名。每个时间帧都会遍历第二个决策树，以获得当时正确的电话的最差情况等级，并为每个时间帧制作一个简短的允许电话列表。快速声学词匹配处理器将来自声学处理器的标签串匹配以产生包括至少一个单词的话语信号。从快速声学匹配和语言模型产生的识别候选中，详细的声匹配将来自声学处理器的标签串与声学词模型相匹配，并输出与发音对应的字串。

6. 发明申请

US20120290299A1 Translating Between Spoken and Written Language 有权
标题翻译：口语和书面语言之间的翻译
公开(公告)号：US20120290299A1
公开(公告)日：2012-11-15
申请号：US13107001
申请日：2011-05-13
申请人： Sara H. Basson , Rick Hamilton , Dan Ning Jiang , Dimitri Kanevsky , David Nahamoo , Michael Picheny , Bhuvana Ramabhadran , Tara N. Sainath
发明人： Sara H. Basson , Rick Hamilton , Dan Ning Jiang , Dimitri Kanevsky , David Nahamoo , Michael Picheny , Bhuvana Ramabhadran , Tara N. Sainath
IPC分类号： G10L15/26
CPC分类号： G06F17/28 , G06F17/2785 , G06F17/289 , G10L15/063 , G10L15/26
摘要： Techniques for converting spoken speech into written speech are provided. The techniques include transcribing input speech via speech recognition, mapping each spoken utterance from input speech into a corresponding formal utterance, and mapping each formal utterance into a stylistically formatted written utterance.
摘要翻译：提供了将语音转换为书面语音的技术。这些技术包括通过语音识别来转录输入语音，将来自输入语音的每个讲话话语映射成对应的形式发音，并将每个正式话语映射成风格格式化的书写话语。

7. 发明申请

US20050119885A1 Speech recognition utilizing multitude of speech features 失效
标题翻译：语音识别利用多种语音特征
公开(公告)号：US20050119885A1
公开(公告)日：2005-06-02
申请号：US10724536
申请日：2003-11-28
申请人： Scott Axelrod , Sreeram Balakrishnan , Stanley Chen , Yuging Gao , Ramesh Gopinath , Hong-Kwang Kuo , Benoit Maison , David Nahamoo , Michael Picheny , George Saon , Geoffrey Zweig
发明人： Scott Axelrod , Sreeram Balakrishnan , Stanley Chen , Yuging Gao , Ramesh Gopinath , Hong-Kwang Kuo , Benoit Maison , David Nahamoo , Michael Picheny , George Saon , Geoffrey Zweig
IPC分类号： G10L15/10 , G10L15/00 , G10L15/02 , G10L15/06 , G10L15/14
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。

8. 发明授权

US08856004B2 Text processing using natural language understanding 有权
公开(公告)号：US08856004B2
公开(公告)日：2014-10-07
申请号：US13107001
申请日：2011-05-13
申请人： Sara H. Basson , Rick Hamilton , Dan Ning Jiang , Dimitri Kanevsky , David Nahamoo , Michael Picheny , Bhuvana Ramabhadran , Tara N. Sainath
发明人： Sara H. Basson , Rick Hamilton , Dan Ning Jiang , Dimitri Kanevsky , David Nahamoo , Michael Picheny , Bhuvana Ramabhadran , Tara N. Sainath
IPC分类号： G10L15/26
CPC分类号： G06F17/28 , G06F17/2785 , G06F17/289 , G10L15/063 , G10L15/26
摘要： Techniques for converting spoken speech into written speech are provided. The techniques include transcribing input speech via speech recognition, mapping each spoken utterance from input speech into a corresponding formal utterance, and mapping each formal utterance into a stylistically formatted written utterance.

9. 发明授权

US09236045B2 Methods and apparatus for proofing of a text input 有权
标题翻译：用于校对文本输入的方法和装置
公开(公告)号：US09236045B2
公开(公告)日：2016-01-12
申请号：US13478930
申请日：2012-05-23
申请人： Martin Labsky , Jan Kleindienst , Tomas Macek , David Nahamoo , Jan Curin , Lars Koenig , Holger Quast
发明人： Martin Labsky , Jan Kleindienst , Tomas Macek , David Nahamoo , Jan Curin , Lars Koenig , Holger Quast
IPC分类号： G10L15/26 , G10L13/08 , G10L15/14 , G06F17/27
CPC分类号： G10L13/08 , G06F17/21 , G06F17/2785 , G10L13/00 , G10L15/01 , G10L15/02 , G10L15/06 , G10L15/14 , G10L15/1822 , G10L15/26 , G10L15/265 , G10L15/28 , G10L15/30 , G10L15/32 , G10L17/00 , G10L21/06
摘要： Techniques for presenting data input as a plurality of data chunks including a first data chunk and a second data chunk. The techniques include converting the plurality of data chunks to a textual representation comprising a plurality of text chunks including a first text chunk corresponding to the first data chunk and a second text chunk corresponding to the second data chunk, respectively, and providing a presentation of at least part of the textual representation such that the first text chunk is presented differently than the second text chunk to, when presented, assist a user in proofing the textual representation.
摘要翻译：用于将数据输入呈现为包括第一数据块和第二数据块的多个数据块的技术。这些技术包括将多个数据块转换成包括多个文本块的文本表示的文本表示，所述文本块包括分别对应于第一数据块的第一文本块和对应于第二数据块的第二文本块，并且提供在文本表示的最少部分，使得第一文本块被呈现与第二文本块不同，当被呈现时，帮助用户校对文本表示。

10. 发明申请

US20120304057A1 METHODS AND APPARATUS FOR CORRECTING RECOGNITION ERRORS 审中-公开
标题翻译：纠正识别错误的方法和设备
公开(公告)号：US20120304057A1
公开(公告)日：2012-11-29
申请号：US13479010
申请日：2012-05-23
申请人： Martin Labsky , Jan Kleindienst , Tomas Macek , David Nahamoo , Jan Curin , William F. Ganong, III
发明人： Martin Labsky , Jan Kleindienst , Tomas Macek , David Nahamoo , Jan Curin , William F. Ganong, III
IPC分类号： G06F17/00
CPC分类号： G10L13/08 , G06F17/21 , G06F17/2785 , G10L13/00 , G10L15/01 , G10L15/02 , G10L15/06 , G10L15/14 , G10L15/1822 , G10L15/26 , G10L15/265 , G10L15/28 , G10L15/30 , G10L15/32 , G10L17/00 , G10L21/06
摘要： Techniques for error correction using a history list comprising at least one misrecognition and correction information associated with each of the at least one misrecognitions indicating how a user corrected the associated misrecognition. The techniques include converting data input from a user to generate a text segment, determining whether at least a portion of the text segment appears in the history list as one of the at least one misrecognitions, if the at least a portion of the text segment appears in the history list as one of the at least one misrecognitions, obtaining the correction information associated with the at least one misrecognition, and correcting the at least a portion of the text segment based, at least in part, on the correction information.
摘要翻译：用于使用历史列表进行纠错的技术包括至少一个与所述至少一个错误识别中的每一个相关联的错误识别和校正信息，指示用户如何更正相关联的误识别。这些技术包括转换从用户输入的数据以生成文本段，确定文本段的至少一部分是否出现在历史列表中作为至少一个错误识别之一，如果文本段的至少一部分出现在所述历史列表中作为所述至少一个错误识别之一，获得与所述至少一个错误识别相关联的所述校正信息，以及至少部分地基于所述校正信息来校正所述文本段的所述至少一部分。

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