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    Method for estimating language model weight and system for the same
    1.
    发明授权
    Method for estimating language model weight and system for the same 失效
    用于估计语言模型权重和系统的方法

    公开(公告)号：US08666739B2

    公开(公告)日：2014-03-04

    申请号：US13324414

    申请日：2011-12-13

    申请人： Hyung Bae Jeon ,  Yun Keun Lee ,  Eui Sok Chung ,  Jong Jin Kim ,  Hoon Chung ,  Jeon Gue Park ,  Ho Young Jung ,  Byung Ok Kang ,  Ki Young Park ,  Sung Joo Lee ,  Jeom Ja Kang ,  Hwa Jeon Song

    发明人： Hyung Bae Jeon ,  Yun Keun Lee ,  Eui Sok Chung ,  Jong Jin Kim ,  Hoon Chung ,  Jeon Gue Park ,  Ho Young Jung ,  Byung Ok Kang ,  Ki Young Park ,  Sung Joo Lee ,  Jeom Ja Kang ,  Hwa Jeon Song

    IPC分类号： G10L15/00

    CPC分类号： G10L15/065 ,  G10L15/187

    摘要： Method of the present invention may include receiving speech feature vector converted from speech signal, performing first search by applying first language model to the received speech feature vector, and outputting word lattice and first acoustic score of the word lattice as continuous speech recognition result, outputting second acoustic score as phoneme recognition result by applying an acoustic model to the speech feature vector, comparing the first acoustic score of the continuous speech recognition result with the second acoustic score of the phoneme recognition result, outputting first language model weight when the first coustic score of the continuous speech recognition result is better than the second acoustic score of the phoneme recognition result and performing a second search by applying a second language model weight, which is the same as the output first language model, to the word lattice.

    摘要翻译： 本发明的方法可以包括接收从语音信号转换的语音特征向量，通过对接收的语音特征向量应用第一语言模型来执行第一搜索，并且将字格的字格和第一声分数输出为连续语音识别结果，输出 第二声学分数作为音素识别结果，通过对语音特征向量应用声学模型，将连续语音识别结果的第一声学分数与音素识别结果的第二声学分数进行比较，当第一个coustic分数输出第一语言模型权重时， 连续语音识别结果比音素识别结果的第二声分数更好，并且通过将与输出第一语言模型相同的第二语言模型权重应用于单词格来进行第二搜索。

    METHOD FOR ESTIMATING LANGUAGE MODEL WEIGHT AND SYSTEM FOR THE SAME
    2.
    发明申请
    METHOD FOR ESTIMATING LANGUAGE MODEL WEIGHT AND SYSTEM FOR THE SAME 失效
    用于估算语言模型重量和系统的方法

    公开(公告)号：US20120150539A1

    公开(公告)日：2012-06-14

    申请号：US13324414

    申请日：2011-12-13

    申请人： Hyung Bae Jeon ,  Yun Keun Lee ,  Eui Sok Chung ,  Jong Jin Kim ,  Hoon Chung ,  Jeon Gue Park ,  Ho Young Jung ,  Byung Ok Kang ,  Ki Young Park ,  Sung Joo Lee ,  Jeom Ja Kang ,  Hwa Jeon Song

    发明人： Hyung Bae Jeon ,  Yun Keun Lee ,  Eui Sok Chung ,  Jong Jin Kim ,  Hoon Chung ,  Jeon Gue Park ,  Ho Young Jung ,  Byung Ok Kang ,  Ki Young Park ,  Sung Joo Lee ,  Jeom Ja Kang ,  Hwa Jeon Song

    IPC分类号： G10L15/00

    CPC分类号： G10L15/065 ,  G10L15/187

    摘要： Method of the present invention may include receiving speech feature vector converted from speech signal, performing first search by applying first language model to the received speech feature vector, and outputting word lattice and first acoustic score of the word lattice as continuous speech recognition result, outputting second acoustic score as phoneme recognition result by applying an acoustic model to the speech feature vector, comparing the first acoustic score of the continuous speech recognition result with the second acoustic score of the phoneme recognition result, outputting first language model weight when the first coustic score of the continuous speech recognition result is better than the second acoustic score of the phoneme recognition result and performing a second search by applying a second language model weight, which is the same as the output first language model, to the word lattice.

    摘要翻译： 本发明的方法可以包括接收从语音信号转换的语音特征向量，通过对接收的语音特征向量应用第一语言模型来执行第一搜索，并且将字格的字格和第一声分数输出为连续语音识别结果，输出 第二声学分数作为音素识别结果，通过对语音特征向量应用声学模型，将连续语音识别结果的第一声学分数与音素识别结果的第二声学分数进行比较，当第一个coustic分数输出第一语言模型权重时， 连续语音识别结果比音素识别结果的第二声分数更好，并且通过将与输出第一语言模型相同的第二语言模型权重应用于单词格来进行第二搜索。

    AIR VENT FOR A VEHICLE
    5.
    发明申请
    AIR VENT FOR A VEHICLE 有权
    一辆车的空中通风

    公开(公告)号：US20130005233A1

    公开(公告)日：2013-01-03

    申请号：US13519231

    申请日：2010-12-27

    申请人： Ki Young Park

    发明人： Ki Young Park

    IPC分类号： B60H1/34

    CPC分类号： B60H1/3421 ,  B60H2001/3464

    摘要： A vehicle air vent includes a plurality of vanes installed in an air discharge port in a body to be rotatable in a horizontal direction. By coupling the vanes to each other, when a knob provided on one vane is operated, all of the vanes are rotated together, and a hinge shaft provided at each of an upper end and a lower end of each vane is inserted into and connected to a hinge hole of a spacer provided at each of an upper end and a lower end of the air discharge port of the air vent body. A damper bushing connected to a front end portion of the vane hinge shaft passing through the hinge hole is installed below the hinge hole of a spacer to which each hinge shaft of the vane provided with the knob is connected.

    摘要翻译： 车辆通风口包括安装在主体中的空气排出口中的多个叶片，以在水平方向上可旋转。 通过将叶片彼此联接，当设置在一个叶片上的旋钮被操作时，所有叶片一起旋转，并且设置在每个叶片的上端和下端中的每一个的铰链轴插入并连接到 设置在排气口的排气口的上端和下端的间隔件的铰链孔。 连接到通过铰链孔的叶片铰链轴的前端部分的阻尼器衬套安装在与设置有旋钮的叶片的每个铰链轴连接的间隔件的铰链孔的下方。

    Air vent for a vehicle
    6.
    发明授权
    Air vent for a vehicle 有权
    车辆通风口

    公开(公告)号：US09358860B2

    公开(公告)日：2016-06-07

    申请号：US13519231

    申请日：2010-12-27

    申请人： Ki Young Park

    发明人： Ki Young Park

    IPC分类号： B60H1/34

    CPC分类号： B60H1/3421 ,  B60H2001/3464

    摘要： A vehicle air vent includes a plurality of vanes installed in an air discharge port in a body to be rotatable in a horizontal direction. By coupling the vanes to each other, when a knob provided on one vane is operated, all of the vanes are rotated together, and a hinge shaft provided at each of an upper end and a lower end of each vane is inserted into and connected to a hinge hole of a spacer provided at each of an upper end and a lower end of the air discharge port of the air vent body. A damper bushing connected to a front end portion of the vane hinge shaft passing through the hinge hole is installed below the hinge hole of a spacer to which each hinge shaft of the vane provided with the knob is connected.

    摘要翻译： 车辆通风口包括安装在主体中的空气排出口中的多个叶片，以在水平方向上可旋转。 通过将叶片彼此联接，当设置在一个叶片上的旋钮被操作时，所有叶片一起旋转，并且设置在每个叶片的上端和下端中的每一个的铰链轴插入并连接到 设置在排气口的排气口的上端和下端的间隔件的铰链孔。 连接到通过铰链孔的叶片铰链轴的前端部分的阻尼器衬套安装在与设置有旋钮的叶片的每个铰链轴连接的间隔件的铰链孔的下方。

    Method for controlling game character
    7.
    发明授权
    Method for controlling game character 失效
    控制游戏角色的方法

    公开(公告)号：US07788194B2

    公开(公告)日：2010-08-31

    申请号：US11690207

    申请日：2007-03-23

    申请人： Ki Young Park ,  Hun Joo Lee ,  Kwang Hyun Shim ,  Kwang Ho Yang

    发明人： Ki Young Park ,  Hun Joo Lee ,  Kwang Hyun Shim ,  Kwang Ho Yang

    IPC分类号： G06N5/00

    CPC分类号： G06N3/02 ,  G06K9/00

    摘要： A method for controlling a game character is provided. The method includes analyzing a game situation in which a character appears; and controlling a behavior of the character depending on a result of the analyzing. Accordingly, situation recognition and behavior control depending on the recognized situation are simultaneously performed using the same algorithm, so that the calculation amount can be reduced, and thus high artificial intelligence can be implemented with less computer resources. Also, a game developer does not need to implement individual behavior rules of characters depending on game situations since a situation of the game may be recognized through learning of an artificial neural network using a game database of game situations, and thus the behavior of characters can be controlled depending on the recognized situation.

    摘要翻译： 提供了一种用于控制游戏角色的方法。 该方法包括分析出现角色的游戏情况; 并根据分析结果来控制角色的行为。 因此，使用相同的算法同时执行根据识别的情况的状况识别和行为控制，从而可以减少计算量，从而可以以更少的计算机资源实现高人造智能。 此外，游戏开发者不需要根据游戏情况实现个人行为规则，因为可以通过使用游戏情境的游戏数据库学习人造神经网络来识别游戏的情况，因此角色的行为可以 根据公认情况进行控制。

    Selective attention method using neural network
    8.
    发明授权
    Selective attention method using neural network 失效
    使用神经网络的选择性注意力方法

    公开(公告)号：US06601052B1

    公开(公告)日：2003-07-29

    申请号：US09598006

    申请日：2000-06-19

    申请人： Soo Young Lee ,  Ki Young Park

    发明人： Soo Young Lee ,  Ki Young Park

    IPC分类号： G06F1518

    CPC分类号： G06K9/6256 ,  G06N3/0454

    摘要： The present invention discloses an implementation of the selective attention mechanism occurring in the human brain using a conventional neural network, multi-layer perceptron and the error back-propagation method as a conventional learning method, and an application of the selective attention mechanism to perception of patterns such as voices or characters. In contrast to the conventional multi-layer perceptron and error back-propagation method in which the weighted value of the network is changed based on a given input signal, the selective attention algorithm of the present invention involves learning a present input pattern to minimize the error of the output layer with the weighted value set to a fixed value, so that the network can receive only a desired input signal to simulate the selective attention mechanism in the aspect of the biology. The present invention also used the selective attention algorithm to define the degree of attention to a plurality of candidate classes as a new criterion for perception, thus providing high perception performance relative to the conventional recognition system for a single candidate class.

    摘要翻译： 本发明公开了使用常规神经网络，多层感知器和误差反向传播方法作为常规学习方法在人脑中发生的选择性注意机制的实现，以及选择性注意机制对感知的应用 模式，如声音或人物。 与其中基于给定输入信号改变网络的加权值的常规多层感知器和误差反向传播方法相反，本发明的选择性关注算法涉及学习当前输入模式以最小化误差 的输出层，其加权值设置为固定值，使得网络可以仅接收期望的输入信号来模拟生物学方面的选择性注意机制。 本发明还使用选择性关注算法来将多个候选类的注意度定义为感知的新标准，从而相对于单个候选类的常规识别系统提供高感知性能。