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1.发明授权Systems and methods that detect a desired signal via a linear discriminative classifier that utilizes an estimated posterior signal-to-noise ratio (SNR) 有权通过利用估计的后验信噪比（SNR）的线性鉴别分类器来检测期望信号的系统和方法，公开(公告)号：US07660713B2
公开(公告)日：2010-02-09
申请号：US10795618
申请日：2004-03-08
IPC分类号： G10L21/00
CPC分类号： G06K9/00536 , G10L25/78
摘要： The present invention provides systems and methods for signal detection and enhancement. The systems and methods utilize one or more discriminative classifiers (e.g., a logistic regression model and a convolutional neural network) to estimate a posterior probability that indicates whether a desired signal is present in a received signal. The discriminative estimators generate the estimated probability based on one or more signal-to-noise ratio (SNRs) (e.g., a normalized logarithmic posterior SNR (nlpSNR) and a mel-transformed nlpSNR (mel-nlpSNR)) and an estimated noise model. Depending on the resolution desired, the estimated SNR can be generated at a frame level or at an atom level, wherein the atom level estimates are utilized to generate the frame level estimate. The novel systems and methods can be utilized to facilitate speech detection, speech recognition, speech coding, noise adaptation, speech enhancement, microphone arrays and echo-cancellation.
摘要翻译： 本发明提供了用于信号检测和增强的系统和方法。 系统和方法利用一个或多个鉴别分类器（例如，逻辑回归模型和卷积神经网络）来估计指示所接收信号中是否存在期望信号的后验概率。 鉴别估计器基于一个或多个信噪比（SNR）（例如，归一化对数后验SNR（nlpSNR）和mel变换的nlpSNR（mel-nlpSNR））和估计的噪声模型来生成估计概率。 根据期望的分辨率，估计的SNR可以在帧级或原子级产生，其中原子级估计用于生成帧级估计。 可以利用新颖的系统和方法来促进语音检测，语音识别，语音编码，噪声适应，语音增强，麦克风阵列和回声消除。
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公开(公告)号：US08103011B2
公开(公告)日：2012-01-24
申请号：US11669549
申请日：2007-01-31
摘要： Signal detectors are described herein. By way of example, a system for detecting signals can include a microphone signal detector, a loudspeaker signal detector, a signal discriminator and a decision component. When the microphone signal detector detects the presence of a microphone signal, the loudspeaker signal detector detects the presence of a loudspeaker signal and the signal discriminator determines that near-end speech dominates loudspeaker echo, the decision component can confirm the presence of doubletalk. When the microphone signal detector detects the presence of a microphone signal and the signal discriminator determines that near-end speech dominates loudspeaker echo, the decision component confirms the presence of near-end signal.
摘要翻译： 这里描述了信号检测器。 作为示例，用于检测信号的系统可以包括麦克风信号检测器，扬声器信号检测器，信号鉴别器和决定部件。 当麦克风信号检测器检测到麦克风信号的存在时，扬声器信号检测器检测到扬声器信号的存在，并且信号鉴别器确定近端语音主导扬声器回波，判定部件可以确认双音节的存在。 当麦克风信号检测器检测到麦克风信号的存在并且信号鉴别器确定近端语音主导扬声器回波时，决定部件确认近端信号的存在。
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3.发明申请公开(公告)号：US20110013781A1
公开(公告)日：2011-01-20
申请号：US12890075
申请日：2010-09-24
IPC分类号： H04B3/20
CPC分类号： H04M9/082
摘要： A regression-based residual echo suppression (RES) system and process for suppressing the portion of the microphone signal corresponding to a playback of a speaker audio signal that was not suppressed by an acoustic echo canceller (AEC). In general, a prescribed regression technique is used between a prescribed spectral attribute of multiple past and present, fixed-length, periods (e.g., frames) of the speaker signal and the same spectral attribute of a current period (e.g., frame) of the echo residual in the output of the AEC. This automatically takes into consideration the correlation between the time periods of the speaker signal. The parameters of the regression can be easily tracked using adaptive methods. Multiple applications of RES can be used to produce better results and this system and process can be applied to stereo-RES as well.
摘要翻译： 基于回归的残差回波抑制（RES）系统和用于抑制对应于未被声学回声消除器（AEC）抑制的扬声器音频信号的重放的麦克风信号的部分的处理。 通常，在多个过去和现在，固定长度的扬声器信号的周期（例如，帧）和当前周期（例如，帧）的相同频谱属性之间使用规定的回归技术 AEC输出中的回波残差。 这自动考虑了扬声器信号的时间段之间的相关性。 可以使用自适应方法轻松跟踪回归的参数。 RES的多个应用可以用于产生更好的结果，并且该系统和过程也可以应用于立体声RES。
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公开(公告)号：US07765212B2
公开(公告)日：2010-07-27
申请号：US11321963
申请日：2005-12-29
CPC分类号： G06Q10/107 , H04L51/00
摘要： A system that facilitates organization of emails comprises a clustering component that clusters a plurality of emails and creates topics for emails by assigning key phrases extracted from emails within one or more clusters. An organization component then utilizes the key phrases to organize documents. Furthermore, the organization component can comprise a probability component that determines a probability that a document belongs to a certain topic.
摘要翻译： 促进电子邮件组织的系统包括：聚类组件，其聚集多个电子邮件，并通过分配从一个或多个集群内的电子邮件中提取的关键短语为电子邮件创建主题。 组织组件然后利用关键短语组织文档。 此外，组织组件可以包括确定文档属于某个主题的概率的概率组件。
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公开(公告)号：US20080181420A1
公开(公告)日：2008-07-31
申请号：US11669549
申请日：2007-01-31
IPC分类号： H04B3/20
摘要： Signal detectors are described herein. By way of example, a system for detecting signals can include a microphone signal detector, a loudspeaker signal detector, a signal discriminator and a decision component. When the microphone signal detector detects the presence of a microphone signal, the loudspeaker signal detector detects the presence of a loudspeaker signal and the signal discriminator determines that near-end speech dominates loudspeaker echo, the decision component can confirm the presence of doubletalk. When the microphone signal detector detects the presence of a microphone signal and the signal discriminator determines that near-end speech dominates loudspeaker echo, the decision component confirms the presence of near-end signal.
摘要翻译： 这里描述了信号检测器。 作为示例，用于检测信号的系统可以包括麦克风信号检测器，扬声器信号检测器，信号鉴别器和决定部件。 当麦克风信号检测器检测到麦克风信号的存在时，扬声器信号检测器检测到扬声器信号的存在，并且信号鉴别器确定近端语音主导扬声器回波，判定部件可以确认双音节的存在。 当麦克风信号检测器检测到麦克风信号的存在并且信号鉴别器确定近端语音主导扬声器回波时，决定部件确认近端信号的存在。
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公开(公告)号：US20090198654A1
公开(公告)日：2009-08-06
申请号：US12141916
申请日：2008-06-19
申请人： Arungunram C. Surendran , John C. Platt , Yi Zhang
发明人： Arungunram C. Surendran , John C. Platt , Yi Zhang
IPC分类号： G06F17/30
CPC分类号： G06Q30/02 , G06F16/313 , G06Q10/10
摘要： A system that facilitates detecting a targeted topic in a document is described herein. The system includes a receiver component that receives a document. The system additionally includes a topic model component trained using a plurality of training documents including the topic and a plurality of training documents that do not include the topic. The topic model component analyzes the document and automatically determines which portions of the document include the topic and which portions of the document do not include the topic.
摘要翻译： 本文描述了便于检测文档中的目标主题的系统。 该系统包括接收文档的接收器组件。 该系统还包括使用包括该主题的多个训练文档训练的主题模型组件和不包括该主题的多个训练文档。 主题模型组件分析文档并自动确定文档的哪些部分包含主题以及文档的哪些部分不包含主题。
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公开(公告)号：US07937264B2
公开(公告)日：2011-05-03
申请号：US11170989
申请日：2005-06-30
IPC分类号： G06F17/27
CPC分类号： G06F17/3071
摘要： A general probabilistic formulation referred to as ‘Conditional Harmonic Mixing’ is provided, in which links between classification nodes are directed, a conditional probability matrix is associated with each link, and where the numbers of classes can vary from node to node. A posterior class probability at each node is updated by minimizing a divergence between its distribution and that predicted by its neighbors. For arbitrary graphs, as long as each unlabeled point is reachable from at least one training point, a solution generally always exists, is unique, and can be found by solving a sparse linear system iteratively. In one aspect, an automated data classification system is provided. The system includes a data set having at least one labeled category node in the data set. A semi-supervised learning component employs directed arcs to determine the label of at least one other unlabeled category node in the data set.
摘要翻译： 提供了称为“条件谐波混合”的一般概率公式，其中分类节点之间的链接被引导，条件概率矩阵与每个链路相关联，并且类的数量可以在节点之间变化。 通过最小化其分布与其邻居预测的分布之间的差异来更新每个节点处的后级概率。 对于任意图，只要每个未标记的点从至少一个训练点到达，则通常总是存在的解是唯一的，并且可以通过迭代地求解稀疏线性系统来找到。 一方面，提供了一种自动数据分类系统。 该系统包括在数据集中具有至少一个标记类别节点的数据集。 半监督学习组件使用有向弧来确定数据集中至少一个其他未标记类别节点的标签。
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公开(公告)号：US06941315B2
公开(公告)日：2005-09-06
申请号：US10602438
申请日：2003-06-23
IPC分类号： G06F17/00 , G06F17/30 , H04Q20060101
CPC分类号： G06F17/30333 , G06F17/30023 , G06F17/30592 , Y10S707/957 , Y10S707/99933 , Y10S707/99942 , Y10S707/99943 , Y10S707/99945 , Y10S707/99948
摘要： Prior to searching a multidimensional feature space populated with data objects, each dimension in the feature space is divided into a number of intervals. When a query is received, a single interval that is overlapped by the query is selected from each dimension. A reduced set of data objects is then selected that includes only those data objects that overlap the selected intervals. This reduced set of data objects, rather than the entire set of data objects in the feature space, is then used to determine matches for the query.
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公开(公告)号：US07379875B2
公开(公告)日：2008-05-27
申请号：US10785560
申请日：2004-02-24
申请人： Christopher J. C. Burges , John C. Platt , Daniel Plastina , Erin L. Renshaw , Henrique S. Malvar
发明人： Christopher J. C. Burges , John C. Platt , Daniel Plastina , Erin L. Renshaw , Henrique S. Malvar
CPC分类号： G11B27/28 , G06F17/30743 , G06F17/30775 , G06K9/00523 , G10H1/00 , G10H1/0008 , G10H2210/061 , G10H2240/131 , G10L25/48 , G11B27/031 , Y10S707/99939
摘要： The present invention relates to a system and methodology to facilitate automatic generation of mnemonic audio portions or segments referred to as audio thumbnails. A system is provided for summarizing audio information. The system includes an analysis component to determine common features in an audio file and a mnemonic detector to extract fingerprint portions of the audio file based in part on the common features in order to generate a thumbnail of the audio file. The generated thumbnails can then be employed to facilitate browsing or searching audio files in order to mitigate listening to longer portions or segments of such files.
摘要翻译： 本发明涉及一种便于自动生成称为音频缩略图的助记音频部分或片段的系统和方法。 提供了一种用于汇总音频信息的系统。 该系统包括用于确定音频文件中的共同特征的分析组件和助记符检测器，以部分地基于公共特征提取音频文件的指纹部分，以便生成音频文件的缩略图。 然后可以使用所生成的缩略图来促进浏览或搜索音频文件，以便减轻对这些文件的较长部分或段的监听。
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公开(公告)号：US07451123B2
公开(公告)日：2008-11-11
申请号：US11296919
申请日：2005-12-08
CPC分类号： G06K9/6276
摘要： Systems and methods are disclosed that facilitate producing probabilistic outputs also referred to as posterior probabilities. The probabilistic outputs include an estimate of classification strength. The present invention intercepts non-probabilistic classifier output and applies a set of kernel models based on a softmax function to derive the desired probabilistic outputs. Such probabilistic outputs can be employed with handwriting recognition where the probability of a handwriting sample classification is combined with language models to make better classification decisions.
摘要翻译： 公开了有助于产生也称为后验概率的概率输出的系统和方法。 概率输出包括分类强度的估计。 本发明拦截非概率分类器输出并且基于softmax函数应用一组核心模型以导出所需的概率输出。 这样的概率输出可以与手写识别一起使用，其中手写样本分类的概率与语言模型组合以进行更好的分类决定。
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