公开(公告)号：US07181090B2

公开(公告)日：2007-02-20

申请号：US10399114

申请日：2001-11-08

Applicant: Matthew J Roach ,  Mark Pawlewski

Inventor： Matthew J Roach ,  Mark Pawlewski

IPC: G06K9/32 ,  G06T13/00

CPC classification number: G06T7/20

Abstract: A method of analysing a sequence of images, for example a sequence of images from a video signal, in which the amount the image changes between two images in a sequence is used to classify the sequence as being either a cartoon or a non cartoon sequence.

Abstract translation: 用于分析图像序列的方法，例如来自视频信号的图像序列，其中图像在序列中的两个图像之间变化的量被用于将序列分类为卡通或非卡通序列。

公开(公告)号：US20130216029A1

公开(公告)日：2013-08-22

申请号：US13877261

申请日：2011-09-27

Applicant: Mark Pawlewski

Inventor： Mark Pawlewski

IPC: H04M3/22

CPC classification number: H04M3/2281 ,  G10L15/26 ,  H04M3/436 ,  H04M2201/41 ,  H04M2203/6027

Abstract: Fraudulent callers that masquerade as legitimate callers in order to discover details of bank accounts or other accounts are an increasing problem. In order to detect possible fraudsters and preventing them from obtaining such details a method and system is proposed that transform the recorded speech of a batch of incoming calls to strings of phonemes or text. Thereafter similar speech patterns, such as distinct similar phrases or wording, in the recorded speech are determined and calls having similar speech patterns, and preferably also similar acoustic properties, are grouped together and identified as being from the same fraudulent caller. Transactions initiated by the fraudulent caller can as a result be stopped and preferably a voiceprint of the fraudulent caller's speech is generated and stored in a database for further use.

Abstract translation: 为了发现银行帐户或其他账户的细节，虚伪的呼叫者伪装成合法的呼叫者是一个越来越多的问题。 为了检测可能的欺诈者并阻止他们获得这样的细节，提出了将一批来电的记录语音转换成音素或文本字符串的方法和系统。 此后，确定记录的语音中类似的语音模式，例如不同的类似的短语或措词，并且具有相似的语音模式，并且优选地也是类似的声学特性的呼叫被分组在一起并被识别为来自相同的欺诈呼叫者。 可以停止由欺诈性呼叫者发起的交易，并且优选地生成欺骗性呼叫者语音的声纹并将其存储在数据库中以供进一步使用。

公开(公告)号：US20110202340A1

公开(公告)日：2011-08-18

申请号：US13126859

申请日：2009-10-29

Applicant: Aladdin M. Ariyaeeinia ,  Surosh G Pillay ,  Mark Pawlewski

Inventor： Aladdin M. Ariyaeeinia ,  Surosh G Pillay ,  Mark Pawlewski

IPC: G10L15/20

CPC classification number: G10L17/12 ,  G10L17/20

Abstract: A speaker verification method is proposed that first builds a general model of user utterances using a set of general training speech data. The user also trains the system by providing a training utterance, such as a passphrase or other spoken utterance. Then in a test phase, the user provides a test utterance which includes some background noise as well as a test voice sample. The background noise is used to bring the condition of the training data closer to that of the test voice sample by modifying the training data and a reduced set of the general data, before creating adapted training and general models. Match scores are generated based on the comparison between the adapted models and the test voice sample, with a final match score calculated based on the difference between the match scores. This final match score gives a measure of the degree of matching between the test voice sample and the training utterance and is based on the degree of matching between the speech characteristics from extracted feature vectors that make up the respective speech signals, and is not a direct comparison of the raw signals themselves. Thus, the method can be used to verify a speaker without necessarily requiring the speaker to provide an identical test phrase to the phrase provided in the training sample.

Abstract translation: 提出了一种说话人验证方法，其首先使用一组一般训练语音数据构建用户话语的一般模型。 用户还通过提供训练话语来训练系统，例如口令或其他口语说话。 然后在测试阶段，用户提供测试话语，其包括一些背景噪声以及测试语音样本。 背景噪声用于在创建适应的训练和一般模型之前，通过修改训练数据和减少的一般数据集，使训练数据的状况更接近于测试语音样本的状态。 基于适应模型和测试语音样本之间的比较产生匹配分数，根据匹配分数之间的差异计算最终匹配分数。 该最终匹配分数给出测试语音样本和训练话语之间的匹配程度的度量，并且基于来自提取的组成各个语音信号的特征向量的语音特征之间的匹配程度，并且不是直接的 原始信号本身的比较。 因此，该方法可用于验证扬声器，而不一定要求扬声器为训练样本中提供的短语提供相同的测试短语。

公开(公告)号：US06389392B1

公开(公告)日：2002-05-14

申请号：US09202026

申请日：1998-12-08

Applicant: Mark Pawlewski ,  Aladdin Mohammad Ariyaeeinia ,  Perasiriyan Sivakumaran

Inventor： Mark Pawlewski ,  Aladdin Mohammad Ariyaeeinia ,  Perasiriyan Sivakumaran

IPC: G10L1700

CPC classification number: G10L17/02 ,  G06K9/6255 ,  G10L17/06

Abstract: A method and apparatus for pattern recognition comprising comparing an input signal representing an unknown pattern with reference data representing each of a plurality of pre-defined patterns, at least one of the pre-defined patterns being represented by at least two instances of reference data. Successive segments of the input signal are compared with successive segments of the reference data and comparison results for each successive segment are generated. For each pre-defined pattern having at least two instances of reference data, the comparison results for the closest matching segment of reference data for each segment of the input signal are recorded to produce a composite comparison result for the said pre-defined pattern. The unknown pattern is the identified on the basis of the comparison results. Thus the effect of a mismatch between the input signal and each instance of the reference data is reduced by selecting the best segments from the instances of reference data for each pre-defined pattern.

Abstract translation: 一种用于模式识别的方法和装置，包括将表示未知模式的输入信号与表示多个预定义模式中的每一个的参考数据进行比较，所述预定义模式中的至少一个由至少两个参考数据实例表示。 将输入信号的连续段与参考数据的连续段进行比较，并生成每个连续段的比较结果。 对于具有至少两个参考数据实例的每个预定义模式，记录输入信号的每个段的参考数据的最接近的匹配段的比较结果，以产生用于所述预定义模式的复合比较结果。 未知模式是根据比较结果确定的。 因此，通过从每个预定义模式的参考数据的实例中选择最佳段来减少输入信号和参考数据的每个实例之间的失配的影响。

公开(公告)号：US09343067B2

公开(公告)日：2016-05-17

申请号：US13126859

申请日：2009-10-29

Applicant: Aladdin M Ariyaeeinia ,  Surosh G Pillay ,  Mark Pawlewski

Inventor： Aladdin M Ariyaeeinia ,  Surosh G Pillay ,  Mark Pawlewski

IPC: G10L15/20 ,  G10L17/12 ,  G10L17/20

CPC classification number: G10L17/12 ,  G10L17/20

Abstract: A speaker verification method is proposed that first builds a general model of user utterances using a set of general training speech data. The user also trains the system by providing a training utterance, such as a passphrase or other spoken utterance. Then in a test phase, the user provides a test utterance which includes some background noise as well as a test voice sample. The background noise is used to bring the condition of the training data closer to that of the test voice sample by modifying the training data and a reduced set of the general data, before creating adapted training and general models. Match scores are generated based on the comparison between the adapted models and the test voice sample, with a final match score calculated based on the difference between the match scores. This final match score gives a measure of the degree of matching between the test voice sample and the training utterance and is based on the degree of matching between the speech characteristics from extracted feature vectors that make up the respective speech signals, and is not a direct comparison of the raw signals themselves. Thus, the method can be used to verify a speaker without necessarily requiring the speaker to provide an identical test phrase to the phrase provided in the training sample.

Abstract translation: 提出了一种说话人验证方法，其首先使用一组一般训练语音数据构建用户话语的一般模型。 用户还通过提供训练话语来训练系统，例如口令或其他口语说话。 然后在测试阶段，用户提供测试话语，其包括一些背景噪声以及测试语音样本。 背景噪声用于在创建适应的训练和一般模型之前，通过修改训练数据和减少的一般数据集，使训练数据的状况更接近于测试语音样本的状态。 基于适应模型和测试语音样本之间的比较产生匹配分数，根据匹配分数之间的差异计算最终匹配分数。 该最终匹配分数给出测试语音样本和训练话语之间的匹配程度的度量，并且基于来自提取的组成各个语音信号的特征向量的语音特征之间的匹配程度，并且不是直接的 原始信号本身的比较。 因此，该方法可用于验证扬声器，而不一定要求扬声器为训练样本中提供的短语提供相同的测试短语。

公开(公告)号：US5583961A

公开(公告)日：1996-12-10

申请号：US105583

申请日：1993-08-13

Applicant: Mark Pawlewski ,  Joseph G. Tang

Inventor： Mark Pawlewski ,  Joseph G. Tang

IPC: G10L15/10 ,  G10L17/02 ,  G10L25/87 ,  G10L5/06 ,  G10L9/00

CPC classification number: G10L25/87 ,  G10L17/02

Abstract: Apparatus and method for speaker recognition includes generating, in response to a speech signal, a plurality of feature data having a series of coefficient sets, each set having a plurality of coefficients indicating the short term special amplitude in a plurality of frequency bands. The feature data is compared with predetermined speaker reference data, and recognition of a corresponding speaker is indicated in dependence upon such comparison. The frequency bands are unevenly spaced along the frequency axis, and a long term average spectral magnitude of at least one of said coefficients is derived and used for normalizing the at least one coefficient.

Abstract translation: 用于说话者识别的装置和方法包括响应于语音信号产生具有一系列系数组的多个特征数据，每个特征数据组具有指示多个频带中的短期特殊幅度的多个系数。 将特征数据与预定的说话者参考数据进行比较，并根据这种比较来指示对应的说话者的识别。 频带沿着频率轴不均匀地间隔，并且导出至少一个所述系数的长期平均频谱幅度，并用于归一化至少一个系数。