公开(公告)号：US4592086A

公开(公告)日：1986-05-27

申请号：US447829

申请日：1982-12-08

申请人： Masao Watari ,  Hiroaki Sakoe

发明人： Masao Watari ,  Hiroaki Sakoe

IPC分类号： G10L15/12 ,  G10L5/06

CPC分类号： G10L15/12

摘要： A continuous speech recognition system determines the similarity between input patterns and reference patterns over time such that similarities between previously spoken speech patterns and reference patterns are determined while speech continues to be spoken. Degrees of dissimilarity at arbitrary reference pattern word times are determined asymptotically and are recorded. The minimum degree of dissimilarity is determined and the corresponding word is categorized. Recognition decisions are ultimately made in reverse chronological order.

摘要翻译： 连续语音识别系统确定输入模式和参考模式随时间的相似性，使得在语音继续被说出的同时确定先前说出的语音模式和参考模式之间的相似性。 任意参考模式字时间的不相似度渐近确定并被记录。 确定最小程度的不相似性并对相应的词进行分类。 识别决定最终按照时间顺序排列。

公开(公告)号：US4319221A

公开(公告)日：1982-03-09

申请号：US153293

申请日：1980-05-27

申请人： Hiroaki Sakoe

发明人： Hiroaki Sakoe

IPC分类号： G10L11/00 ,  G06K9/64 ,  G10L15/00 ,  G10L15/12 ,  G06K9/00 ,  G10L1/00

CPC分类号： G10L15/12 ,  G06K9/6206 ,  G10L15/00

摘要： A similarity calculator for calculating a set of similarity measures S(A(u, m), B.sup.c)'s according to the technique of dynamic programming comprises an input pattern buffer for successively producing input pattern feature vectors of an input pattern A to be pattern matched with reference patterns B.sup.c, an m-th input pattern feature vector a.sub.m at a time. The similarity measure set is for a set of fragmentary patterns A(u, m)'s defined by a common end point m and start points u's predetermined relative to the end point m. Scalar products (a.sub.m .multidot.b.sub.j.sup.n) are calculated between the m-th input pattern feature vector and reference pattern feature vectors b.sub.j.sup.n of an n-th reference pattern B.sup.n and stored in a scalar product buffer. Recurrence values are calculated according to a recurrence formula for each end point m, rather than for each fragmentary pattern set, and for each reference pattern B.sup.n to provide a similarity measure subset S(A(u, m), B.sup.n)'s, with a recurrence value for each reference pattern feature vector b.sub.v calculated by the use of the scalar product (a.sub.m .multidot.b.sub.v) and recurrence values calculated for a previous end point (m-1) and for at least three consecutive reference pattern feature vectors preselected relative to that reference pattern feature vector b.sub.v. Instead of the scalar product, it is possible to use any one of other measures representative of a similarity or a dissimilarity between an input pattern feature vector and a reference pattern feature vector.

摘要翻译： 用于根据动态规划技术计算一组相似性度量S（A（u，m），Bc））的相似度计算器包括：输入图案缓冲器，用于连续产生要被输入的输入图案A的输入图案特征向量 与参考图案Bc匹配，一次是第m个输入图案特征向量am。 相似性度量集是针对由公共终点m和相对于终点m预定的起始点u定义的一组零碎图案A（u，m）。 在第m个输入图案特征向量和第n个参考图案Bn的参考图案特征向量bjn之间计算标量产品（amxbjn），并存储在标量积缓冲器中。 根据每个终点m的递归公式而不是针对每个分段模式集计算复现值，并且对于每个参考模式Bn，提供相似性度量子集S（A（u，m），Bn） 通过使用标量积（amxbv）计算的每个参考图形特征向量bv的递归值和针对先前终点（m-1）计算的重复值以及相对于该参考预先选择的至少三个连续的参考模式特征向量 模式特征向量bv。 代替标量积，可以使用表示输入模式特征向量和参考模式特征向量之间的相似性或不相似性的其他度量中的任一种。

公开(公告)号：US4286115A

公开(公告)日：1981-08-25

申请号：US058598

申请日：1979-07-18

申请人： Hiroaki Sakoe

发明人： Hiroaki Sakoe

IPC分类号： G10L11/00 ,  G10L15/00 ,  G10L15/12 ,  G10L15/18 ,  G10L1/00

CPC分类号： G10L15/12 ,  G10L15/00

摘要： A continuous speech recognition system utilizes a format memory (14) which specifies a sequence of word sets and a plurality of words, or reference patterns, which may be included in each word set. The input pattern sequence is divided into all possible partial patterns having start points p and end points q, and each of these partial patterns is compared with all reference patterns to derive elementary similarity measures. The elementary similarity measures for each combination of a partial pattern and a permitted word in a word set under the specified format are then examined to determine the optimum input pattern segmentation points and corresponding sequence of reference patterns which will yield a maximum similarity result. The maximum similarity is represented by ##EQU1## where S(p(x-1), p(x),n(x)) indicates the degree of similarity between an input partial pattern having a start point p(x-1) and an n point p(x) and a reference word unit n(x) within a word set f.sub.x, and K represents the number of word sets permitted according to the specified format.

摘要翻译： 连续语音识别系统利用格式存储器（14），该格式存储器（14）指定可以包括在每个单词集合中的单词集合和多个单词或参考模式的序列。 将输入图案序列分为具有起始点p和终点q的所有可能的部分图案，并且将这些部分图案中的每一个与所有参考图案进行比较以导出基本相似性度量。 然后检查在指定格式下的单词集合中的部分模式和允许字的每个组合的基本相似度度量，以确定将产生最大相似性结果的最佳输入模式分割点和相应的参考模式序列。 最大相似度由表示，其中S（p（x-1），p（x），n（x））表示具有起始点p（x-1）和 单词集fx内的n点p（x）和参考单元n（x），K表示根据指定格式允许的单词集合的数量。

公开(公告)号：US4049913A

公开(公告)日：1977-09-20

申请号：US737454

申请日：1976-11-01

申请人： Hiroaki Sakoe

发明人： Hiroaki Sakoe

IPC分类号： G06F17/27 ,  G06F17/28 ,  G10L15/00 ,  G10L15/12 ,  G10L1/00

CPC分类号： G06F17/2715 ,  G06F17/277 ,  G10L15/00 ,  G10L15/12

摘要： A continuous speech recognition system comprises a word number specifier for specifying, as the number of continuously spoken word or words, either a single integer or a set of different integers. The single integer may be manually or automatically adjusted. In compliance with the specified word number or numbers, the system carries out pattern matching between an input pattern representative of the spoken word or words and a predetermined number of reference patterns. The matching may be carried into effect by dynamic programming. The input pattern is recognized to be one of the reference patterns or to be a concatenation of some or all of the reference patterns, equal in number either to the single integer or to one of the different integers.

摘要翻译： 连续语音识别系统包括用于指定连续说出的单词或单词的数目是单个整数或一组不同整数的字数说明符。 单个整数可以手动或自动调整。 根据指定的字号或数字，系统执行表示说出的单词或单词的输入模式与预定数量的参考模式之间的模式匹配。 匹配可以通过动态规划来实现。 输入模式被识别为参考模式之一，或者是某些或所有参考模式的级联，其数量与单个整数或不同整数之一相等。

公开(公告)号：US4975961A

公开(公告)日：1990-12-04

申请号：US263208

申请日：1988-10-27

申请人： Hiroaki Sakoe

发明人： Hiroaki Sakoe

IPC分类号： G06N3/04 ,  G06N3/10 ,  G10L15/12 ,  G10L15/16

CPC分类号： G06N3/04 ,  G06N3/10 ,  G10L15/12 ,  G10L15/16

摘要： In a neural network, input neuron units of an input layer are grouped into first through J-th input layer frames, where J represents a predetermined natural number. Intermediate neuron units of an intermediate layer are grouped into first through J-th intermediate layer frames. An output layer comprises an output neuron unit. Each intermediate neuron unit of a j-th intermediate layer frame is connected to the input neuron units of j'-th input layer frames, where j is variable between 1 and j and j' represents at least two consecutive integers, one of which is equal to j and at least one other of which is less than j. Each output neuron unit is connected to the intermediate neuron units of the intermediate layer. For recognition of an input pattern represented by a time sequence of feature vectors, each consisting of K vector components, where K represents a predetermined positive integer, each input layer frame consists of K input neuron units. Each intermediate layer frame consists of M intermediate neuron units, where M represents a positive integer which is less than K. The vector components of each feature vector are supplied to the respective input neuron units of one of the input layer frames that is preferably selected from three consecutively numbered input layer frames. The neural network is readily trained to make a predetermined one of the output neuron units produce an output signal indicative of the input pattern and can be implemented by a microprocessor.

公开(公告)号：US4555796A

公开(公告)日：1985-11-26

申请号：US448088

申请日：1982-12-09

申请人： Hiroaki Sakoe

发明人： Hiroaki Sakoe

IPC分类号： G10L11/00 ,  G06F17/30 ,  G10L15/12 ,  G10L15/18 ,  G10L5/00

CPC分类号： G06F17/30985 ,  G10L15/12

摘要： A connected word recognition system operable according to a DP algorithm and in compliance with a regular grammar, is put into operation in synchronism with successive specification of feature vectors of an input pattern. In an m-th period in which an m-th feature vector is specified, similarity measures are calculated (58, 59) between reference patterns representative of reference words and those fragmentary patterns of the input pattern, which start at several previous periods and end at the m-th period, for start and end states of the reference words. In the m-th period, an extremum of the similarity measures is found (66, 69, 86), together with a particular word and a particular pair of start and end states thereof, and stored (61-63). Moreover, a particular start period is selected (67, 86) and stored (64). A previous extremum found and stored (61) during the (m-1)-th period for the particular start state found in the (m-1)-th period, is used in the m-th period as a boundary condition in calculating each similarity measure. After all input pattern feature vectors are processed, a result of recognition is obtained (89) by referring to the stored extrema, particular words, particular start states, and particular start periods.

摘要翻译： 根据DP算法可操作并且符合常规语法的连接词识别系统与输入模式的特征向量的连续指定同步地投入运行。 在指定第m个特征向量的第m个周期中，计算表示参考词的参考模式与输入模式的那些片段模式之间的相似性度量（58,59），其从先前的几个周期开始，并且结束 在第m个时期，参考词的开始和结束状态。 在第m个时期，发现相似性度量的极值（66,69,86），连同一个特定的单词和一个特定的一对开始和结束状态，并被存储（61-63）。 此外，选择特定的开始周期（67,86）并存储（64）。 在第（m-1）个周期中发现的特定开始状态的第（m-1）个周期期间发现和存储的先前极值（61）在第m个周期中被用作计算的边界条件 每个相似性度量。 在所有输入模式特征向量被处理之后，通过参考所存储的极值，特定的单词，特定的起始状态和特定的起始周期来获得识别的结果（89）。

公开(公告)号：US4326101A

公开(公告)日：1982-04-20

申请号：US175798

申请日：1980-08-06

申请人： Hiroaki Sakoe

发明人： Hiroaki Sakoe

IPC分类号： G10L11/00 ,  G10L15/00 ,  G10L15/12 ,  G10L15/18 ,  G10L1/00

CPC分类号： G10L15/12 ,  G10L15/00

摘要： Operation of a continuous speech recognition system operable according to the dynamic programming technique, is controlled by a state transition diagram in compliance with which word sequences to be recognized by the system with reference to a predetermined number of reference words B.sup.n 's are pronounced. The system comprises a state transition table accessed by the reference words B.sup.n 's to successively produce particular states y's in the diagram and previous states z's for each particular state y. In cooperation with a recurrence value and an optimum parameter table, a matching unit determines a recurrence value T.sub.y (m) and an optimum parameter set ZUN.sub.y (m) according to: ##EQU1## where u and m represent an end and a start point of a fragmentary pattern A(u, m) of an input pattern A representative of a word sequence and D(u, m, n), a similarity measure between the fragmentary pattern A(u, m) and a reference word B.sup.n assigned to a permutation of the previous and the particular states z and y. By referring to the optimum parameter table and, as the case may be, to the recurrence value table, a decision unit recognizes the word sequence as a concatenation of optimum ones of the reference words B.sup.n 's.

摘要翻译： 可以根据动态编程技术操作的连续语音识别系统的操作由状态转换图来控制，该状态转换图符合系统参考预定数量的参考词Bn的哪个字序列被发音。 该系统包括由参考词Bn's访问的状态转换表，以连续地产生图中的特定状态y和每个特定状态y的先前状态z。 根据递归值和最优参数表，匹配单元根据：Ty（m）= min或max [Tz（u）+ D）确定递归值Ty（m）和最优参数集ZUNy（m） （u，m，n）] z，u，n和ZUNy（m）= arg min或max [Tz（u）+ D（u，m，n）]，z，u，n其中u和m表示 （u，m）和D（u，m，n）之间的相似性度量，以及分段模式A（u，m）和 参考字Bn被分配给先前的特定状态和特定状态z和y的置换。 通过参考最优参数表，并且视情况而定，对于递归值表，判定单元将该单词序列识别为最佳参考词Bn's的级联。

公开(公告)号：US4239936A

公开(公告)日：1980-12-16

申请号：US974274

申请日：1978-12-28

申请人： Hiroaki Sakoe

发明人： Hiroaki Sakoe

IPC分类号： G10L11/02 ,  G10L15/20 ,  G10L1/00 ,  H03G3/32

CPC分类号： G10L25/87 ,  G10L15/20

摘要： A speech recognition system adaptable to noisy environments is disclosed. The system includes a recognition unit for recognizing input speech signals and a noise measuring unit for measuring the intensity of ambient noises. The system also includes a rejection unit responsive to a rejection standard controlled by the intensity of the measured noise for rejecting the rejection results given from the recognition unit when the rejection standard is exceeded.

摘要翻译： 公开了适用于嘈杂环境的语音识别系统。 该系统包括用于识别输入语音信号的识别单元和用于测量环境噪声强度的噪声测量单元。 该系统还包括响应于由所测量的噪声的强度控制的拒收标准的拒收单元，用于当超过拒绝标准时拒绝从识别单元给出的拒绝结果。

公开(公告)号：US4872201A

公开(公告)日：1989-10-03

申请号：US657428

申请日：1984-10-03

申请人： Hiroaki Sakoe

发明人： Hiroaki Sakoe

IPC分类号： G10L11/00 ,  G06K9/62 ,  G06T7/00 ,  G10L15/00 ,  G10L15/12

CPC分类号： G10L15/12 ,  G10L15/00

摘要： A pattern matching apparatus for comparing an input pattern of features with a reference pattern. Address information is stored in the reference pattern along with features, so that branching in a work memory which stores cumulative distances between the input and reference patterns may be effected. In this manner, memory requirements for storing reference patterns are reduced, and the number of required distance calculations also is reduced.

摘要翻译： 一种用于将特征的输入图案与参考图案进行比较的图案匹配装置。 地址信息与特征一起存储在参考图案中，使得可以实现存储输入和参考图案之间的累积距离的工作存储器中的分支。 以这种方式，减少用于存储参考图案的存储器要求，并且减少所需距离计算的数量。

公开(公告)号：US4581755A

公开(公告)日：1986-04-08

申请号：US436978

申请日：1982-10-27

申请人： Hiroaki Sakoe

发明人： Hiroaki Sakoe

IPC分类号： G10L11/00 ,  G10L15/10 ,  G10L15/20 ,  G10L17/00 ,  G10L1/00

CPC分类号： G10L15/10

摘要： There is provided a voice recognition system comprising a standard pattern memory in which a voice pattern of a predetermined word is stored as a positive reference pattern and also voice patterns of words similar to but different from the first-mentioned word are stored as negative reference patterns, a pattern comparator for calculating dissimilarities of an input voice pattern with respect to the positive reference pattern and negative reference patterns, and a discriminator for providing a coincidence confirmation output signal when the dissimilarity with respect to the positive reference pattern is less than a predetermined threshold value and less than the dissimilarities with respect to the negative reference patterns while otherwise rejecting the result of recognition.

摘要翻译： 提供了一种包括标准图案存储器的语音识别系统，其中预定字的语音图案被存储为正参考图案，并且还将与第一提到的单词相似但不同的单词的语音模式存储为负参考模式 ，用于计算相对于正参考图案和负参考图案的输入声音图案的不相似性的图案比较器，以及当相对于正参考图案的相异性小于预定阈值时提供重合确认输出信号的鉴别器 价值，而不是相对于负参考模式的不同之处，否则拒绝承认结果。