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1. 发明授权

US06801155B2 Method and apparatus for recognising a radar target 失效
标题翻译：用于识别雷达目标的方法和装置
公开(公告)号：US06801155B2
公开(公告)日：2004-10-05
申请号：US10333630
申请日：2003-01-23
申请人： Mohammed Jahangir , Keith M Ponting
发明人： Mohammed Jahangir , Keith M Ponting
IPC分类号： G01S7292
CPC分类号： G06K9/6297 , G01S7/2923 , G01S7/415 , G01S13/524 , G06K9/3241
摘要： A method of recognizing a radar target comprises producing a sequence of Doppler spectra of radar returns form a scene and producing therefrom a sequence of Doppler feature vectors for a target in the scene. Hidden Markov modelling (HMM) is then used to identify the sequence of Doppler feature vectors as indicating a member of a particular class of targets. HMM is used to identify the sequence of Doppler feature vectors by assigning to each feature vector an occurrence probability by selecting a probability distribution or state from a set thereof associated with a class of targets, multiplying the occurrence probabilities together to obtain an overall probability, repeating for other probability distributions in the set to determine a combination of probability distributions giving highest overall probability for that class of target, then repeating for at least one other class of targets and selecting the target class as being that which yields the highest overall occurrence probability.
摘要翻译：识别雷达目标的方法包括从场景产生雷达返回的多普勒频谱序列，并由此产生场景中的目标的多普勒特征向量序列。然后使用隐马尔可夫模型（HMM）来识别多普勒特征向量的序列，以指示特定类别的目标的成员。 HMM用于通过从与特定类别的目标相关联的集合中选择概率分布或状态来向每个特征向量分配发生概率来识别多普勒特征向量的序列，将发生概率相乘以获得总概率，重复对于集合中的其他概率分布来确定给出该类目标的最高总概率的概率分布的组合，然后针对至少一个其他类别的目标重复，并且将目标类别选择为产生最高总发生概率的目标类别。

2. 发明授权

US08209171B2 Methods and apparatus relating to searching of spoken audio data 有权
标题翻译：与搜索口语音频数据有关的方法和设备
公开(公告)号：US08209171B2
公开(公告)日：2012-06-26
申请号：US12222381
申请日：2008-08-07
申请人： Martin G Abbott , Keith M Ponting
发明人： Martin G Abbott , Keith M Ponting
IPC分类号： G10L15/00
CPC分类号： G10L15/187
摘要： This invention relates to a method of searching spoken audio data for one or more search terms comprising performing a phonetic search of the audio data to identify likely matches to a search term and producing textual data corresponding to a portion of the spoken audio data including a likely match. An embodiment of the method comprises the steps of taking phonetic index data corresponding to the spoken audio data, searching the phonetic index data for likely matches to the search term, wherein when a likely match is detected a portion of the spoken audio data or phonetic index data is selected which includes the likely match and said selected portion of the spoken audio data or phonetic index data is processed using a large vocabulary speech recognizer. The large vocabulary speech recognizer may derive textual data which can be used for further processing or may be used to present a transcript to a user. The present invention therefore combines the benefit of phonetic searching of audio data with the advantages of large vocabulary speech recognition.
摘要翻译：本发明涉及一种搜索一个或多个搜索词汇的语音数据的方法，包括执行音频数据的语音搜索以识别对搜索词的可能匹配，并产生对应于口语音频数据的一部分的文本数据，包括可能的比赛。该方法的一个实施例包括以下步骤：对应于所述口语音频数据的语音索引数据;搜索所述语音索引数据与所述搜索词的可能匹配;其中，当检测到可能的匹配时，所述口语音频数据或语音索引的一部分选择包括可能匹配的数据，并且使用大词汇语音识别器来处理口头音频数据或语音索引数据的所述选定部分。大词汇语音识别器可以导出可以用于进一步处理的文本数据，或者可以用于向用户呈现抄本。因此，本发明将音频数据的语音搜索的优点与大词汇语音识别的优点相结合。

3. 发明授权

US06671666B1 Recognition system 有权
标题翻译：识别系统
公开(公告)号：US06671666B1
公开(公告)日：2003-12-30
申请号：US09381571
申请日：1999-08-24
申请人： Keith M Ponting , Robert W Series , Michael J Tomlinson
发明人： Keith M Ponting , Robert W Series , Michael J Tomlinson
IPC分类号： G10L1520
CPC分类号： G10L15/065 , G10L15/142 , G10L15/20
摘要： A recognition system (10) incorporates a filterbank analyser (16) producing successive data vectors of energy values for twenty-six frequency intervals in a speech signal. A unit (18) compensates for spectral distortion in each vector. Compensated vectors undergo a transformation into feature vectors with twelve dimensions and are matched with hidden Markov model states in a computer (24). Each matched model state has a mean value which is an estimate of the speech feature vector. A match inverter (28) produces an estimate of the speech data vector in frequency space by a pseudo-inverse transformation. It includes information which will be lost in a later transformation to frequency space. The estimated data vector is compared with its associated speech signal data vector, and infinite impulse response filters (44) average their difference with others. Averaged difference vectors so produced are used by the unit (18) in compensation of speech signal data vectors.
摘要翻译：识别系统（10）包括滤波器组分析器（16），其在语音信号中产生二十六个频率间隔的能量值的连续数据向量。单元（18）补偿每个矢量中的频谱失真。补偿矢量经历了具有十二维度的特征向量的变换，并与计算机中的隐马尔可夫模型状态相匹配（24）。每个匹配模型状态具有作为语音特征向量的估计的平均值。匹配反相器（28）通过伪逆变换产生频率空间中的语音数据矢量的估计。它包括将在以后的变换到频率空间中丢失的信息。将估计的数据矢量与其相关联的语音信号数据矢量进行比较，无限脉冲响应滤波器（44）平均与其他数据矢量的差异。如此产生的平均差分矢量由单元（18）用于补偿语音信号数据矢量。

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