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    • 31. 发明申请
    • System and method of separating signals
    • 分离信号的系统和方法
    • US20050149462A1
    • 2005-07-07
    • US10949710
    • 2004-09-24
    • Te-Won LeeMichael LewickiTerrence Sejnowski
    • Te-Won LeeMichael LewickiTerrence Sejnowski
    • G06E1/00G06E3/00G06F15/00G06F15/18G06G7/00G06K9/62H03F1/26H04B15/00
    • G06K9/624
    • A computer-implemented method and apparatus that adapts class parameters, classifies data and separates sources configured in one of multiple classes whose parameters (i.e. characteristics) are initially unknown. A mixture model is used in which the observed data is categorized into two or more mutually exclusive classes. The class parameters for each of the classes are adapted to a data set in an adaptation algorithm in which class parameters including mixing matrices and bias vectors are adapted. Each data vector is assigned to one of the learned mutually exclusive classes. The adaptation and classification algorithms can be utilized in a wide variety of applications such as speech processing, image processing, medical data processing, satellite data processing, antenna array reception, and information retrieval systems.
    • 一种计算机实现的方法和装置,其适应类参数,对数据进行分类并分离在其参数(即特征)最初未知的多个类之一中配置的源。 使用混合模型,其中观察到的数据被分类为两个或更多个互斥类。 每个类的类参数适应于适配算法中的数据集,其中包括混合矩阵和偏置向量的类参数被适配。 每个数据向量被分配给学习的互斥类之一。 适应和分类算法可以用于诸如语音处理,图像处理,医疗数据处理,卫星数据处理,天线阵列接收和信息检索系统的各种应用中。
    • 32. 发明授权
    • System and method of separating signals
    • 分离信号的系统和方法
    • US06799170B2
    • 2004-09-28
    • US10202190
    • 2002-07-22
    • Te-Won LeeMichael S. LewickiTerrence J. Sejnowski
    • Te-Won LeeMichael S. LewickiTerrence J. Sejnowski
    • G06N302
    • G06K9/624G06K9/6807G10L21/0272
    • A computer-implemented method and apparatus that adapts class parameters, classifies data and separates sources configured in one of multiple classes whose parameters (i.e. characteristics) are initially unknown. A mixture model is used in which the observed data is categorized into two or more mutually exclusive classes. The class parameters for each of the classes are adapted to a data set in an adaptation algorithm in which class parameters including mixing matrices and bias vectors are adapted. Each data vector is assigned to one of the learned mutually exclusive classes. The adaptation and classification algorithms can be utilized in a wide variety of applications such as speech processing, image processing, medical data processing, satellite data processing, antenna array reception, and information retrieval systems.
    • 一种计算机实现的方法和装置,其适应类参数,对数据进行分类并分离在其参数(即特征)最初未知的多个类之一中配置的源。 使用混合模型,其中观察到的数据被分类为两个或更多个互斥类。 每个类的类参数适应于适配算法中的数据集,其中包括混合矩阵和偏置向量的类参数被适配。 每个数据向量被分配给学习的互斥类之一。 适应和分类算法可以用于诸如语音处理,图像处理,医疗数据处理,卫星数据处理,天线阵列接收和信息检索系统的各种应用中。
    • 33. 发明授权
    • Touchless sensing and gesture recognition using continuous wave ultrasound signals
    • 使用连续波超声信号进行无触摸感测和手势识别
    • US08907929B2
    • 2014-12-09
    • US12885151
    • 2010-09-17
    • Ren LiTe-Won LeeHui-ya L. NelsonSamir K Gupta
    • Ren LiTe-Won LeeHui-ya L. NelsonSamir K Gupta
    • G06F3/043G09G3/10G01S7/527G06F3/01G01S15/87G01S15/50G01S15/32
    • G06F3/011G01S7/5273G01S15/325G01S15/50G01S15/876G06F3/017
    • The embodiments provide systems and methods for touchless sensing and gesture recognition using continuous wave sound signals. Continuous wave sound, such as ultrasound, emitted by a transmitter may reflect from an object, and be received by one or more sound receivers. Sound signals may be temporally encoded. Received sound signals may be processed to determine a channel impulse response or calculate time of flight. Determined channel impulse responses may be processed to extract recognizable features or angles. Extracted features may be compared to a database of features to identify a user input gesture associated with the matched feature. Angles of channel impulse response curves may be associated with an input gesture. Time of flight values from each receiver may be used to determine coordinates of the reflecting object. Embodiments may be implemented as part of a graphical user interface. Embodiments may be used to determine a location of an emitter.
    • 这些实施例提供了使用连续波声信号的无接触感测和手势识别的系统和方法。 由发射器发射的连续波声,如超声波,可能会从物体反射,并由一个或多个声音接收器接收。 声音信号可能是时间编码的。 可以处理接收的声音信号以确定信道脉冲响应或计算飞行时间。 可以处理确定的信道脉冲响应以提取可识别的特征或角度。 提取的特征可以与特征数据库进行比较,以识别与匹配特征相关联的用户输入手势。 信道脉冲响应曲线的角度可以与输入手势相关联。 可以使用来自每个接收机的飞行时间值来确定反射对象的坐标。 实施例可以被实现为图形用户界面的一部分。 实施例可以用于确定发射器的位置。
    • 34. 发明申请
    • Separation of target acoustic signals in a multi-transducer arrangement
    • 在多换能器布置中分离目标声信号
    • US20050060142A1
    • 2005-03-17
    • US10897219
    • 2004-07-22
    • Erik VisserTe-Won Lee
    • Erik VisserTe-Won Lee
    • G10L21/02
    • H04R3/005G10L21/0208G10L21/0272G10L2021/02161G10L2021/02165H04R2430/25
    • The present invention provides a process for separating a good quality information signal from a noisy acoustic environment. The separation process uses a set of a least two spaced-apart transducers to capture noise and information components. The transducer signals, which have both a noise and information component, are received into a separation process. The separation process generates one channel that is substantially only noise, and another channel that is a combination of noise and information. An identification process is used to identify which channel has the information component. The noise signal is then used to set process characteristics that are applied to the combination signal to efficiently reduce or eliminate the noise component. In this way, the noise is effectively removed from the combination signal to generate a good qualify information signal. The information signal may be, for example, a speech signal, a seismic signal, a sonar signal, or other acoustic signal.
    • 本发明提供了一种用于从良好的声学环境中分离出良好质量信息信号的方法。 分离过程使用一组至少两个间隔开的传感器来捕获噪声和信息分量。 具有噪声和信息分量的换能器信号被接收到分离过程中。 分离过程产生基本上只有噪声的一个信道,以及作为噪声和信息的组合的另一个信道。 使用识别过程来识别哪个信道具有信息分量。 然后使用噪声信号来设置施加到组合信号的处理特性,以有效地减少或消除噪声分量。 以这种方式,有效地从组合信号中去除噪声以产生良好的限定信息信号。 信息信号可以是例如语音信号,地震信号,声纳信号或其他声信号。
    • 37. 发明申请
    • VOICE ACTIVITY DETECTION BASED ON PLURAL VOICE ACTIVITY DETECTORS
    • 基于多个语音活动检测器的语音活动检测
    • US20110208520A1
    • 2011-08-25
    • US12711943
    • 2010-02-24
    • Te-Won Lee
    • Te-Won Lee
    • G10L15/20
    • G10L25/78
    • A voice activity detection (VAD) system includes a first voice activity detector, a second voice activity detector and control logic. The first voice activity detector is included in a device and produces a first VAD signal. The second voice activity detector is located externally to the device and produces a second VAD signal. The control logic combines the first and second VAD signals into a VAD output signal. Voice activity may be detected based on the VAD output signal. The second VAD signal can be represented as a flag included in a packet containing digitized audio. The packet can be transmitted to the device from the externally located VAD over a wireless link.
    • 语音活动检测(VAD)系统包括第一语音活动检测器,第二语音活动检测器和控制逻辑。 第一语音活动检测器被包括在设备中并产生第一VAD信号。 第二语音活动检测器位于设备外部并产生第二VA​​D信号。 控制逻辑将第一和第二VAD信号组合成VAD输出信号。 可以基于VAD输出信号检测语音活动。 第二VAD信号可以被表示为包含在包含数字化音频的分组中的标志。 该分组可以通过无线链路从外部定位的VAD发送到设备。
    • 39. 发明申请
    • System and method for speech processing using independent component analysis under stability restraints
    • 在稳定性约束下使用独立分量分析进行语音处理的系统和方法
    • US20060053002A1
    • 2006-03-09
    • US10537985
    • 2003-12-11
    • Erik VisserTe-Won Lee
    • Erik VisserTe-Won Lee
    • G10L11/00
    • G10L21/0272
    • A system and method for separating a mixture of audio signal into desired audio signals (430) (e.g., speech) and a noise sign (440) is disclosed. Microphones (310, 320) are positioned to receive the mixed audio signals, and an independent component analysis (ICA) processes (212) the sound mixture using stability constraints. The ICA process (508) uses predefined characteristics of the desired speech signal to identify and isolate a target sound signal (430). Filter coefficients are adapted with a learning rule and filter weight update dynamics are stabilized to assist convergence to a stable separated ICA signal result. The separated signals may be peripherally-processed to further reduce noise effects using post-processing (214) and pre-processing (220, 230) techniques and information. The proposed system is designed and easily adaptable for implementation on DSP units or CPUs in audio communication hardware environments.
    • 公开了一种用于将音频信号的混合分离成所需音频信号(430)(例如语音)和噪声信号(440)的系统和方法。 麦克风(310,320)被定位成接收混合音频信号,并且独立分量分析(ICA)使用稳定性约束来处理(212)声音混合。 ICA处理(508)使用所需语音信号的预定特征来识别和隔离目标声音信号(430)。 滤波器系数适应于学习规则,并且滤波器权重更新动态被稳定以辅助收敛到稳定的分离的ICA信号结果。 可以对分离的信号进行外围处理,以进一步减少使用后处理(214)和预处理(220,230)技术和信息的噪声影响。 所提出的系统设计和易于适应于在音频通信硬件环境中的DSP单元或CPU上的实现。
    • 40. 发明授权
    • Method and apparatus for efficiently encoding chromatic images using non-orthogonal basis functions
    • 使用非正交基函数有效地编码彩色图像的方法和装置
    • US06870962B2
    • 2005-03-22
    • US09846485
    • 2001-04-30
    • Te-Won LeeThomas WachtlerTerrence J. Sejnowski
    • Te-Won LeeThomas WachtlerTerrence J. Sejnowski
    • G06T9/00H03M7/30H04N1/41H04N7/30G06K9/36G06K9/46
    • G06K9/6242G06K9/4652G06T9/007
    • A method and apparatus for efficiently encoding images using a set of non-orthogonal basis functions, thereby allowing reduction of file size, shorter transmission time, and improved accuracy. The non-orthogonal basis functions include homogenous color basis functions, luminance-encoding basis functions that have luminance edges and chromatic basis functions that exhibit color opponency. Some of the basis functions are non-orthogonal with respect to each other. Using these basis functions, a source vector is calculated to provide a number of coefficients, each coefficient associated with one basis function. The source vector is compressed by selecting a subset of the calculated coefficients, thereby providing an encoded vector. Because the method is highly efficient, the image data is substantially represented by a small number of coefficients. In some embodiments, the non-orthogonal basis functions include two or more classes. A wavelet approach can also be utilized.
    • 一种用于使用一组非正交基函数对图像进行高效编码的方法和装置,从而允许减小文件大小,缩短传输时间和提高精度。 非正交基函数包括均匀颜色基函数,具有亮度边缘的亮度编码基函数和表现色彩对立的色基函数。 一些基本函数相互之间是非正交的。 使用这些基函数,计算源向量以提供多个系数,每个系数与一个基函数相关联。 通过选择所计算的系数的子集来压缩源向量,由此提供编码的向量。 因为该方法是高效的,所以图像数据基本上由少量系数表示。 在一些实施例中,非正交基函数包括两个或多个类。 也可以使用小波方法。