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    Method and apparatus for estimating noise by using harmonics of voice signal
    12.
    发明授权
    Method and apparatus for estimating noise by using harmonics of voice signal 有权
    通过使用语音信号的谐波估计噪声的方法和装置

    公开(公告)号：US08135586B2

    公开(公告)日：2012-03-13

    申请号：US12053144

    申请日：2008-03-21

    Applicant: Hyun-Soo Kim ,  Hanseok Ko ,  Sung-Joo Ahn ,  Jounghoon Beh ,  Hyun-Jin Yoon

    Inventor： Hyun-Soo Kim ,  Hanseok Ko ,  Sung-Joo Ahn ,  Jounghoon Beh ,  Hyun-Jin Yoon

    IPC: G10L19/10

    CPC classification number: G10L21/0208

    Abstract: Disclosed is a method and an apparatus for estimating noise included in a sound signal during sound signal processing. The method includes estimating harmonics components in a frame of an input sound signal; using the estimated harmonics components, computing a Voice Presence Probability (VPP) on the frame of the input sound signal; determining a weight of an equation necessary to estimate a noise spectrum, depending on the computed VPP; and using the determined weight and the equation necessary to estimate a noise spectrum, estimating the noise spectrum, and updating the noise spectrum.

    Abstract translation: 公开了一种用于在声音信号处理期间估计包括在声音信号中的噪声的方法和装置。 该方法包括估计输入声音信号的帧中的谐波分量; 使用估计的谐波分量，在输入声音信号的帧上计算声音概率（VPP）; 根据所计算的VPP确定估计噪声谱所必需的方程的权重; 并且使用所确定的权重和所需的等式来估计噪声谱，估计噪声谱和更新噪声谱。

    Face recognition system and method based on adaptive learning
    13.
    发明授权
    Face recognition system and method based on adaptive learning 有权
    基于自适应学习的人脸识别系统和方法

    公开(公告)号：US08135220B2

    公开(公告)日：2012-03-13

    申请号：US12115250

    申请日：2008-05-05

    Applicant: Hyun-Soo Kim ,  Je-Han Yoon ,  Hyun-Sik Shim ,  Young-Hee Park ,  Do-Hyung Kim ,  Woo-Han Yun

    Inventor： Hyun-Soo Kim ,  Je-Han Yoon ,  Hyun-Sik Shim ,  Young-Hee Park ,  Do-Hyung Kim ,  Woo-Han Yun

    IPC: G06K9/62 ,  G06K9/00

    CPC classification number: G06K9/00295

    Abstract: A face recognition system based on adaptive learning includes a specific person detection and tracking unit for detecting and tracking a specific person from a moving image. A facial feature extraction unit extracts a plurality of facial feature vectors from the detected and tracked specific person. A face recognition unit searches for a given registration model by comparing the extracted facial feature vectors with facial feature vectors of the registration models previously stored in a user registration model database. A learning target selection unit selects a facial feature vector to be added to a record of the given registration model from among the extracted facial feature vectors. A registration model learning unit adds and updates the selected facial feature vector to the record of the given registration model.

    Abstract translation: 基于自适应学习的面部识别系统包括用于从运动图像中检测和跟踪特定人物的特定人物检测和跟踪单元。 面部特征提取单元从检测到和跟踪的特定人物中提取多个面部特征向量。 面部识别单元通过将提取的面部特征向量与先前存储在用户登记模型数据库中的登记模型的面部特征向量进行比较来搜索给定的登记模型。 学习目标选择单元从所提取的面部特征向量中选择要添加到给定登记模型的记录的面部特征向量。 注册模型学习单元将所选择的面部特征向量添加并更新到给定注册模型的记录。

    Method and system for aligning windows to extract peak feature from a voice signal
    14.
    发明授权
    Method and system for aligning windows to extract peak feature from a voice signal 有权
    用于对齐窗口以从语音信号中提取峰值特征的方法和系统

    公开(公告)号：US08103512B2

    公开(公告)日：2012-01-24

    申请号：US11656873

    申请日：2007-01-23

    Applicant: Hyun-Soo Kim

    Inventor： Hyun-Soo Kim

    IPC: G10L19/00

    CPC classification number: G10L25/90

    Abstract: Disclosed is a method capable of adaptively aligning windows to extract features according to the types and characteristics of voice signals. To this end, window lengths based on the window update points in a corresponding order are determined by employing the concept of a higher order peak, and windows are aligned according to window lengths. When the windows are aligned according to such a manner, the start and end points of each window is known, so that it becomes possible to easily extract and analyze peak feature information.

    Abstract translation: 公开了一种能够根据语音信号的类型和特性自适应地对齐窗口以提取特征的方法。 为此，通过采用高阶峰值的概念来确定基于相应顺序的窗口更新点的窗口长度，并且根据窗口长度对准窗口。 当窗口按照这种方式对齐时，每个窗口的开始和结束点是已知的，从而可以容易地提取和分析峰值特征信息。

    Sound processing apparatus and method
    15.
    发明授权
    Sound processing apparatus and method 有权
    声音处理装置及方法

    公开(公告)号：US08073148B2

    公开(公告)日：2011-12-06

    申请号：US11479472

    申请日：2006-06-30

    Applicant: Hyun-Soo Kim

    Inventor： Hyun-Soo Kim

    IPC: A61F11/06

    CPC classification number: G10L21/0208

    Abstract: Disclosed is an apparatus and method for processing signals such as sound signals. The sound processing apparatus includes a sound signal input unit for receiving sound signals, a harmonic noise separator for separating a harmonic region and a noise region from the received sound signals, a noise restraint index determination unit for determining an optimal noise restraint index k according to a system and circumstance, and a noise restrainer for restraining the separated noise region depending on the noise restraint index k so as to output noise attenuated signals.

    Abstract translation: 公开了一种用于处理诸如声音信号的信号的装置和方法。 声音处理装置包括：用于接收声音信号的声音信号输入单元，用于从接收的声音信号中分离谐波区域和噪声区域的谐波噪声分离器;噪声抑制指标确定单元，用于根据 系统和环境，以及用于根据噪声抑制指数k抑制分离的噪声区域以便输出噪声衰减信号的噪声抑制器。

    METHOD AND APPARATUS FOR PRODUCING DYNAMIC EFFECT OF CHARACTER CAPABLE OF INTERACTING WITH IMAGE
    17.
    发明申请
    METHOD AND APPARATUS FOR PRODUCING DYNAMIC EFFECT OF CHARACTER CAPABLE OF INTERACTING WITH IMAGE 审中-公开
    用于产生与图像交互的字符的动态效应的方法和装置

    公开(公告)号：US20110193867A1

    公开(公告)日：2011-08-11

    申请号：US13025724

    申请日：2011-02-11

    Applicant: Hee-Bum AHN ,  Hyun-Soo Kim ,  Mu-Sik Kwon ,  Sang-Wook Oh ,  Dong-Hyuk Lee ,  Seong-Taek Hwang ,  An-Na Park

    Inventor： Hee-Bum AHN ,  Hyun-Soo Kim ,  Mu-Sik Kwon ,  Sang-Wook Oh ,  Dong-Hyuk Lee ,  Seong-Taek Hwang ,  An-Na Park

    IPC: G06T13/00

    CPC classification number: G06T13/80

    Abstract: A method for producing motion effects of a character capable of interacting with a background image in accordance with the characteristics of the background image is provided, including extracting the characteristics of the background image; determining a character to be provided with the motion effects in the background in accordance with the extracted characteristics of the background image; recognizing external signals including a user input; determining the motion of the character in accordance with the characteristics of the background image and the recognized external signals; and reproducing an animation for executing the motion of the character in the background image.

    Abstract translation: 提供一种用于产生能够根据背景图像的特征与背景图像进行交互的角色的运动效果的方法，包括提取背景图像的特征; 根据所提取的背景图像的特征确定要在背景中提供运动效果的角色; 识别包括用户输入的外部信号; 根据背景图像和识别的外部信号的特性确定角色的运动; 并且再现用于执行背景图像中的角色的运动的动画。

    Apparatus and method for video sensor-based human activity and facial expression modeling and recognition
    19.
    发明申请
    Apparatus and method for video sensor-based human activity and facial expression modeling and recognition 有权
    基于视频传感器的人类活动和面部表情建模与识别的装置和方法

    公开(公告)号：US20100310157A1

    公开(公告)日：2010-12-09

    申请号：US12802381

    申请日：2010-06-04

    Applicant: Hyun-Soo Kim ,  Jong-Chang Lee ,  Dae-Hyun Sim ,  Tae-Seong Kim

    Inventor： Hyun-Soo Kim ,  Jong-Chang Lee ,  Dae-Hyun Sim ,  Tae-Seong Kim

    IPC: G06K9/62 ,  G06K9/46

    CPC classification number: G06K9/00315 ,  G06K9/00335 ,  G06K9/00342 ,  G06K9/6232 ,  G06K9/6255 ,  G06K9/6297

    Abstract: An apparatus and method for human activity and facial expression modeling and recognition are based on feature extraction techniques from time sequential images. The human activity modeling includes determining principal components of depth and/or binary shape images of human activities extracted from video clips. Independent Component Analysis (ICA) representations are determined based on the principal components. Features are determined through Linear Discriminant Analysis (LDA) based on the ICA representations. A codebook is determined using vector quantization. Observation symbol sequences in the video clips are determined. And human activities are learned using the Hidden Markov Model (HMM) based on status transition and an observation matrix.

    Abstract translation: 用于人类活动和面部表情建模和识别的装置和方法基于来自时间顺序图像的特征提取技术。 人类活动建模包括确定从视频剪辑中提取的人类活动的深度和/或二进制形状图像的主要分量。 独立成分分析（ICA）表示是基于主成分确定的。 特征通过基于ICA表示的线性判别分析（LDA）来确定。 使用矢量量化确定码本。 确定视频剪辑中的观察符号序列。 并且使用基于状态转换的隐马尔科夫模型（HMM）和观察矩阵来学习人类活动。

    Speech signal classification system and method
    20.
    发明授权
    Speech signal classification system and method 有权
    语音信号分类系统及方法

    公开(公告)号：US07809555B2

    公开(公告)日：2010-10-05

    申请号：US11725588

    申请日：2007-03-19

    Applicant: Hyun-Soo Kim

    Inventor： Hyun-Soo Kim

    IPC: H04J3/17 ,  H04B14/06 ,  G06F15/00 ,  G10L15/20 ,  G10L21/00

    CPC classification number: G10L25/93

    Abstract: Provided is a speech signal classification system and method. The speech signal classification system includes a primary recognition unit for determining using characteristics extracted from a speech frame whether the speech frame is a voice sound, a non-voice sound, or background noise and a secondary recognition unit for determining using at least one other speech frame whether a determination-reserved speech frame is an non-voice sound or background noise, if it is determined according to a primary recognition result that an input speech frame is not a voice sound. The system reserves a determination of the input speech frame, stores characteristics of at least one other speech frame to determine the determination-reserved speech frame, calculates secondary statistical values from characteristics of the determination-reserved speech frame and the stored characteristics of the other speech frames, and determines using the calculated secondary statistical values whether the determination-reserved speech frame is an non-voice sound or background noise. Accordingly, if an input speech frame is not a voice sound, the input speech frame can be more accurately classified and output as an non-voice sound or background noise, and thus errors, which may be generated in determination of a signal corresponding to an non-voice sound, can be reduced.

    Abstract translation: 提供了一种语音信号分类系统和方法。 语音信号分类系统包括主识别单元，用于确定使用从语音帧提取的特征，无论语音帧是语音，非声音还是背景噪声，以及辅助识别单元，用于使用至少一个其他语音来确定 如果根据主要识别结果确定输入的语音帧不是语音，则确定确定预留语音帧是否是非语音声音或背景噪声。 系统保留输入语音帧的确定，存储至少一个其他语音帧的特征以确定确定保留的语音帧，根据确定保留的语音帧的特性和存储的另一个语音的特性来计算辅助统计值 并且使用所计算的二次统计值来确定所述确定预留语音帧是否是非声音或背景噪声。 因此，如果输入语音帧不是声音，则可以更准确地将输入语音帧分类并输出为非语音或背景噪声，从而可以在确定对应于 非声音，可以减少。

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