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    • 1. 发明授权
    • Methods and apparatus for performing speech recognition using acoustic models which are improved through an interactive process
    • 使用通过交互过程改善的声学模型进行语音识别的方法和装置
    • US06263308B1
    • 2001-07-17
    • US09531055
    • 2000-03-20
    • David E. HeckermanFileno A. AllevaRobert L. RounthwaiteDaniel RosenMei-Yuh HwangYoram YaacoviJohn L. Manferdelli
    • David E. HeckermanFileno A. AllevaRobert L. RounthwaiteDaniel RosenMei-Yuh HwangYoram YaacoviJohn L. Manferdelli
    • G10L1502
    • G10L15/063
    • Automated methods and apparatus for synchronizing audio and text data, e.g., in the form of electronic files, representing audio and text expressions of the same work or information are described. Also described are automated methods of detecting errors and other discrepancies between the audio and text versions of the same work. A speech recognition operation is performed on the audio data initially using a speaker independent acoustic model. The recognized text in addition to audio time stamps are produced by the speech recognition operation. The recognized text is compared to the text in text data to identify correctly recognized words. The acoustic model is then retrained using the correctly recognized text and corresponding audio segments from the audio data transforming the initial acoustic model into a speaker trained acoustic model. The retrained acoustic model is then used to perform an additional speech recognition operation on the audio data. The audio and text data are synchronized using the results of the updated acoustic model. In addition, one or more error reports based on the final recognition results are generated showing discrepancies between the recognized words and the words included in the text. By retraining the acoustic model in the above described manner, improved accuracy is achieved.
    • 描述用于同步音频和文本数据的自动方法和装置,例如以电子文件的形式,表示相同作品或信息的音频和文本表达。 还描述了检测相同作品的音频和文本版本之间的错误和其他差异的自动化方法。 首先使用与扬声器无关的声学模型对音频数据执行语音识别操作。 通过语音识别操作产生除音频时间戳之外的识别文本。 将识别的文本与文本数据中的文本进行比较,以识别正确识别的字词。 然后使用来自音频数据的正确识别的文本和对应的音频段将声学模型再训练,将初始声学模型变换成扬声器训练的声学模型。 然后再训练的声学模型用于对音频数据执行附加的语音识别操作。 使用更新的声学模型的结果来同步音频和文本数据。 此外,生成基于最终识别结果的一个或多个错误报告,显示识别的单词与文本中包含的单词之间的差异。 通过以上述方式重新训练声学模型,实现了提高的精度。
    • 2. 发明授权
    • Methods and apparatus for automatically synchronizing electronic audio files with electronic text files
    • 电子音频文件与电子文本文件自动同步的方法和装置
    • US06260011B1
    • 2001-07-10
    • US09531054
    • 2000-03-20
    • David E. HeckermanFileno A. AllevaRobert L. RounthwaiteDaniel RosenMei-Yuh HwangYoram YaacoviJohn L. Manferdelli
    • David E. HeckermanFileno A. AllevaRobert L. RounthwaiteDaniel RosenMei-Yuh HwangYoram YaacoviJohn L. Manferdelli
    • G10L1508
    • H04N21/466G06F17/30017G09B5/062G10L15/08G10L15/26H04N21/4307H04N21/435H04N21/4394H04N21/8106H04N21/8133
    • Automated methods and apparatus for synchronizing audio and text data, e.g., in the form of electronic files, representing audio and text expressions of the same work or information are described. A statistical language model is generated from the text data. A speech recognition operation is then performed on the audio data using the generated language model and a speaker independent acoustic model. Silence is modeled as a word which can be recognized. The speech recognition operation produces a time indexed set of recognized words some of which may be silence. The recognized words are globally aligned with the words in the text data. Recognized periods of silence, which correspond to expected periods of silence, and are adjoined by one or more correctly recognized words are identified as points where the text and audio files should be synchronized, e.g., by the insertion of bi-directional pointers. In one embodiment, for a text location to be identified for synchronization purposes, both words which bracket, e.g., precede and follow, the recognized silence must be correctly identified. Pointers, corresponding to identified locations of silence to be used for synchronization purposes are inserted into the text and/or audio files at the identified locations. Audio time stamps obtained from the speech recognition operation may be used as the bi-directional pointers. Synchronized text and audio data may be output in a variety of file formats.
    • 描述用于同步音频和文本数据的自动方法和装置,例如以电子文件的形式,表示相同作品或信息的音频和文本表达。 从文本数据生成统计语言模型。 然后使用生成的语言模型和与扬声器无关的声学模型对音频数据执行语音识别操作。 沉默被模仿为可以被认可的一个词。 语音识别操作产生识别字的时间索引集合,其中一些可能是静音。 识别的单词与文本数据中的单词全局对齐。 识别的静音期间,其对应于预期的沉默期,并且被一个或多个正确识别的字相邻,被识别为文本和音频文件应当被同步的点,例如通过插入双向指针。 在一个实施例中,对于要为同步目的被识别的文本位置,必须正确地识别包括例如先前和后面的两个单词。 对应于要用于同步目的的所确定的沉默位置的指针被插入到所识别位置的文本和/或音频文件中。 从语音识别操作获得的音频时间戳可以用作双向指针。 可以以各种文件格式输出同步的文本和音频数据。
    • 6. 发明授权
    • Trees of classifiers for detecting email spam
    • 用于检测电子邮件垃圾邮件的分类树
    • US07930353B2
    • 2011-04-19
    • US11193691
    • 2005-07-29
    • David M. ChickeringGeoffrey J. HultenRobert L. RounthwaiteChristopher A. MeekDavid E. HeckermanJoshua T. Goodman
    • David M. ChickeringGeoffrey J. HultenRobert L. RounthwaiteChristopher A. MeekDavid E. HeckermanJoshua T. Goodman
    • G06F15/16
    • H04L51/12
    • Decision trees populated with classifier models are leveraged to provide enhanced spam detection utilizing separate email classifiers for each feature of an email. This provides a higher probability of spam detection through tailoring of each classifier model to facilitate in more accurately determining spam on a feature-by-feature basis. Classifiers can be constructed based on linear models such as, for example, logistic-regression models and/or support vector machines (SVM) and the like. The classifiers can also be constructed based on decision trees. “Compound features” based on internal and/or external nodes of a decision tree can be utilized to provide linear classifier models as well. Smoothing of the spam detection results can be achieved by utilizing classifier models from other nodes within the decision tree if training data is sparse. This forms a base model for branches of a decision tree that may not have received substantial training data.
    • 利用分类器模型填充的决策树利用电子邮件的每个功能使用单独的电子邮件分类器来提供增强的垃圾邮件检测。 这通过定制每个分类器模型提供了更高的垃圾邮件检测的概率,以便于在逐个特征的基础上更准确地确定垃圾邮件。 分类器可以基于诸如逻辑回归模型和/或支持向量机(SVM)等线性模型来构建。 分类器也可以基于决策树构建。 基于决策树的内部和/或外部节点的“复合特征”也可以用于提供线性分类器模型。 垃圾邮件检测结果的平滑可以通过使用来自决策树内的其他节点的分类器模型来实现,如果训练数据是稀疏的。 这形成了可能没有接收到大量训练数据的决策树的分支的基本模型。
    • 7. 发明授权
    • Message rendering for identification of content features
    • 消息渲染用于识别内容功能
    • US07483947B2
    • 2009-01-27
    • US10428649
    • 2003-05-02
    • Bryan T. StarbuckRobert L. RounthwaiteDavid E. HeckermanJoshua T. Goodman
    • Bryan T. StarbuckRobert L. RounthwaiteDavid E. HeckermanJoshua T. Goodman
    • G06F15/16
    • G06Q10/107H04L51/12
    • Architecture for detecting and removing obfuscating clutter from the subject and/or body of a message, e.g., e-mail, prior to filtering of the message, to identify junk messages commonly referred to as spam. The technique utilizes the powerful features built into an HTML rendering engine to strip the HTML instructions for all non-substantive aspects of the message. Pre-processing includes pre-rendering of the message into a final format, which final format is that which is displayed by the rendering engine to the user. The final format message is then converted to a text-only format to remove graphics, color, non-text decoration, and spacing that cannot be rendered as ASCII-style or Unicode-style characters. The result is essentially to reduce each message to its common denominator essentials so that the junk mail filter can view each message on an equal basis.
    • 用于在过滤消息之前检测和去除来自主体和/或消息主体(例如电子邮件)的模糊杂波的体系结构,以识别通常被称为垃圾邮件的垃圾邮件。 该技术利用内置于HTML呈现引擎中的强大功能来剥离消息的所有非实质性方面的HTML指令。 预处理包括将消息预渲染成最终格式,最终格式是由呈现引擎向用户显示的最终格式。 最终格式化消息然后转换为纯文本格式以删除不能以ASCII样式或Unicode风格字符呈现的图形,颜色,非文本装饰和间距。 结果基本上是将每个消息减少到其公分要素,以便垃圾邮件过滤器可以在平等的基础上查看每个消息。
    • 8. 发明申请
    • MESSAGE RENDERING FOR IDENTIFICATION OF CONTENT FEATURES
    • 用于识别内容特征的消息呈现
    • US20100088380A1
    • 2010-04-08
    • US12359126
    • 2009-01-23
    • Bryan T. StarbuckRobert L. RounthwaiteDavid E. HeckermanJoshua T. Goodman
    • Bryan T. StarbuckRobert L. RounthwaiteDavid E. HeckermanJoshua T. Goodman
    • G06F21/00G06F15/16
    • G06Q10/107H04L51/12
    • Architecture for detecting and removing obfuscating clutter from the subject and/or body of a message, e.g., e-mail, prior to filtering of the message, to identify junk messages commonly referred to as spam. The technique utilizes the powerful features built into an HTML rendering engine to strip the HTML instructions for all non-substantive aspects of the message. Pre-processing includes pre-rendering of the message into a final format, which final format is that which is displayed by the rendering engine to the user. The final format message is then converted to a text-only format to remove graphics, color, non-text decoration, and spacing that cannot be rendered as ASCII-style or Unicode-style characters. The result is essentially to reduce each message to its common denominator essentials so that the junk mail filter can view each message on an equal basis.
    • 用于在过滤消息之前检测和去除来自主体和/或消息主体(例如电子邮件)的模糊杂波的体系结构,以识别通常被称为垃圾邮件的垃圾邮件。 该技术利用内置于HTML呈现引擎中的强大功能来剥离消息的所有非实质性方面的HTML指令。 预处理包括将消息预渲染成最终格式,最终格式是由呈现引擎向用户显示的最终格式。 最终格式化消息然后转换为纯文本格式以删除不能以ASCII样式或Unicode风格字符呈现的图形,颜色,非文本装饰和间距。 结果基本上是将每个消息减少到其公分要素,以便垃圾邮件过滤器可以在平等的基础上查看每个消息。
    • 9. 发明授权
    • Adaptive junk message filtering system
    • 自适应垃圾邮件过滤系统
    • US07640313B2
    • 2009-12-29
    • US11779263
    • 2007-07-17
    • Robert L. RounthwaiteJoshua T. GoodmanDavid E. HeckermanJohn C. PlattCarl M. Kadie
    • Robert L. RounthwaiteJoshua T. GoodmanDavid E. HeckermanJohn C. PlattCarl M. Kadie
    • G06F15/16G06F15/173
    • G06Q10/107H04L51/12
    • The invention relates to a system for filtering messages—the system includes a seed filter having associated therewith a false positive rate and a false negative rate. A new filter is also provided for filtering the messages, the new filter is evaluated according to the false positive rate and the false negative rate of the seed filter, the data used to determine the false positive rate and the false negative rate of the seed filter are utilized to determine a new false positive rate and a new false negative rate of the new filter as a function of threshold. The new filter is employed in lieu of the seed filter if a threshold exists for the new filter such that the new false positive rate and new false negative rate are together considered better than the false positive and the false negative rate of the seed filter.
    • 本发明涉及一种用于过滤消息的系统 - 该系统包括具有与其相关联的假阳性率和假阴性率的种子滤波器。 还提供了一种过滤消息的新过滤器,根据种子过滤器的假阳性率和假阴性率评估新过滤器,用于确定种子过滤器的假阳性率和假阴性率的数据 用于确定新过滤器的新的假阳性率和新的假阴性率作为阈值的函数。 如果新的过滤器存在阈值,则使用新的过滤器来代替种子过滤器,使得新的假阳性率和新的假阴性率一起被认为优于种子过滤器的假阳性率和假阴性率。
    • 10. 发明授权
    • Adaptive junk message filtering system
    • 自适应垃圾邮件过滤系统
    • US07249162B2
    • 2007-07-24
    • US10374005
    • 2003-02-25
    • Robert L. RounthwaiteJoshua T. GoodmanDavid E. HeckermanJohn C. PlattCarl M. Kadie
    • Robert L. RounthwaiteJoshua T. GoodmanDavid E. HeckermanJohn C. PlattCarl M. Kadie
    • G06F15/16
    • G06Q10/107H04L51/12
    • The invention relates to a system for filtering messages—the system includes a seed filter having associated therewith a false positive rate and a false negative rate. A new filter is also provided for filtering the messages, the new filter is evaluated according to the false positive rate and the false negative rate of the seed filter, the data used to determine the false positive rate and the false negative rate of the seed filter are utilized to determine a new false positive rate and a new false negative rate of the new filter as a function of threshold. The new filter is employed in lieu of the seed filter if a threshold exists for the new filter such that the new false positive rate and new false negative rate are together considered better than the false positive and the false negative rate of the seed filter.
    • 本发明涉及一种用于过滤消息的系统 - 该系统包括具有与其相关联的假阳性率和假阴性率的种子滤波器。 还提供了一种过滤消息的新过滤器,根据种子过滤器的假阳性率和假阴性率评估新过滤器,用于确定种子过滤器的假阳性率和假阴性率的数据 用于确定新过滤器的新的假阳性率和新的假阴性率作为阈值的函数。 如果新的过滤器存在阈值,则使用新的过滤器来代替种子过滤器,使得新的假阳性率和新的假阴性率一起被认为优于种子过滤器的假阳性率和假阴性率。