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    • 4. 发明公开
    • 사전 데이터 압축 방법
    • 压缩字数据的方法
    • KR1020050044399A
    • 2005-05-12
    • KR1020047007121
    • 2002-11-08
    • 노키아 코포레이션
    • 티안질레이
    • G10L15/14
    • G10L15/12G10L2015/025H03M7/30
    • The invention relates to pre-processing of a pronunciation dictionary for compression in a data processing device, the pronunciation dictionary comprising at least one entry, the entry comprising a sequence of character units and a sequence of phoneme units. According to one aspect of the invention the sequence of character units and the sequence of phoneme units are aligned using a statistical algorithm. The aligned sequence of character units and aligned sequence of phoneme units are interleaved by inserting each phoneme unit at a predetermined location relative to the corresponding character unit.
    • 本发明涉及一种用于在数据处理设备中进行压缩的发音字典的预处理,该发音字典包括至少一个条目,该条目包括一系列字符单元和一系列音素单元。 根据本发明的一个方面,使用统计算法来对齐字符单元的序列和音素单元的序列。 通过将每个音素单元相对于相应的字符单元插入预定位置来交织字符单元的排列顺序和对准的音素单元的顺序。
    • 5. 发明授权
    • 동적 타임 워핑 디바이스와 이를 이용한 음성 인식 장치
    • 동적타임워핑디바이스와이를이용한음성인식장치
    • KR100462472B1
    • 2004-12-17
    • KR1020020054940
    • 2002-09-11
    • 학교법인 포항공과대학교
    • 정홍김용
    • G10L15/12
    • G10L15/12
    • Provided are a dynamic time warping device using speech recognition software, and a speech recognition apparatus using the same. The dynamic time warping device includes memory units for processing characterization vectors of a test pattern and a predetermined reference pattern using a FIFO queue, and a plurality of processing elements serially connected to each other, the plurality of processing elements multiplying a predetermined weight by a difference between the characterization vectors of the test and reference patterns, which are obtained by shifting them in the opposite directions, adding the multiplication result to matching cost values of adjacent nodes, and comparing the addition results to detect the smallest matching cost value. Accordingly, fast speech recognition can be realized by embedding speech recognition software using a dynamic time warping algorithm into hardware. Also, it is possible to increase a recognition rate of speech by adjusting weight according to a node to be compared, and provide a dynamic time warping device that can be mass-produced as application-specification integrated circuits (ASICs). Further, a compact speech recognition apparatus using the dynamic time warping device can be provided without requiring a computer to drive software for speech recognition.
    • 提供了一种使用语音识别软件的动态时间规整装置以及使用该装置的语音识别装置。 动态时间伸缩装置包括用于使用FIFO队列来处理测试模式的特征向量和预定参考模式的存储器单元以及彼此串联连接的多个处理元件,多个处理元件将预定权重乘以差值 通过在相反方向上移动它们获得的测试和参考模式的特征向量之间,将相乘结果添加到相邻节点的匹配成本值,并比较相加结果以检测最小匹配成本值。 因此,通过使用动态时间规整算法将语音识别软件嵌入到硬件中可以实现快速语音识别。 而且,可以通过根据要比较的节点调整权重来提高语音的识别率,并且提供可以作为应用规范集成电路(ASIC)批量生产的动态时间规整装置。 此外,可以提供使用动态时间规整装置的小型语音识别装置,而不需要计算机驱动用于语音识别的软件。
    • 8. 发明公开
    • 노이즈 편집을 이용한 그래픽스 객체 편집 기법
    • 使用噪声编辑编辑图形对象
    • KR1020060133847A
    • 2006-12-27
    • KR1020050053717
    • 2005-06-21
    • 이인권
    • 이인권윤종철
    • G06T5/00
    • H04N21/4307G06T15/205G06T2219/2021G10L15/12
    • A method for editing graphical objects by noise editing is provided to calculate result values for user's noise restriction demands while keeping statistic characteristics of noise by optimization for minimizing a difference between an ideal statistic value and a statistic value of gradient value of a real noise function. In a method for editing graphical objects by noise editing, M 3D PRN unit vectors are composed to be stored in a G table, which has M size, and M-1 random number permutations from P to O are stored in another table having the same size. 3 integer intervals[qi0,qi1](i=1,2,3) for each dimension of given coordinates are obtained, wherein qi0=[xi]mod M and qi0=qi1+1. The 3 integer intervals generate a single regular tetrahedron. 8 gradient vectors are obtained for each point of the calculated regular tetrahedron: gjkl=G[P[P[Pq1j]+q2k+q3l]], wherein jkl represent all permutations from 0 to 1 having a length of 3. A result value of noise is calculated by calculation of 8 inner products, that is, a weighted sum of gjklÀ[vjkl-(x1,x2,x3)], wherein the weighted sum is calculated by ease curve formula represented by s(t)=6t5-15t4+10t3.
    • 提供了一种通过噪声编辑编辑图形对象的方法,以通过优化来保持理想统计值和实际噪声函数的梯度值的统计值之间的差异来保持用户的噪声限制需求的结果值,同时保持噪声的统计特性。 在通过噪声编辑编辑图形对象的方法中,将M 3D PRN单元向量存储在具有M大小的G表中,并且将从P到O的M-1个随机数排列存储在具有相同的表中 尺寸。 获得给定坐标的每个维度的3个整数间隔[qi0,qi1](i = 1,2,3),其中qi0 = x mod M和qi0 = qi1 + 1。 3个整数间隔产生单个正四面体。 对于计算的正四面体的每个点获得8个梯度向量:gjkl = G [P [P [Pq1j] + q2k + q3l]],其中jkl表示从0到1的长度为3的所有排列。 通过计算8个内积,即gjkl- [x1,x2,x3]]的加权和来计算噪声,其中通过由s(t)= 6t5-15t4表示的简化曲线公式计算加权和 + 10t3。