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    • 1. 发明授权
    • System and method for partitioning the feature space of a classifier in
a pattern classification system
    • US6058205A
    • 2000-05-02
    • US781574
    • 1997-01-09
    • Lalit Rai BahlPeter Vincent deSouzaDavid NahamooMukund Padmanabhan
    • Lalit Rai BahlPeter Vincent deSouzaDavid NahamooMukund Padmanabhan
    • G06K9/62G06F17/20
    • G06K9/6282
    • A system and method are provided which partition the feature space of a classifier by using hyperplanes to construct a binary decision tree or hierarchical data structure for obtaining the class probabilities for a particular feature vector. One objective in the construction of the decision tree is to minimize the average entropy of the empirical class distributions at each successive node or subset, such that the average entropy of the class distributions at the terminal nodes is minimized. First, a linear discriminant vector is computed that maximally separates the classes at any particular node. A threshold is then chosen that can be applied on the value of the projection onto the hyperplane such that all feature vectors that have a projection onto the hyperplane that is less than the threshold are assigned to a child node (say, left child node) and the feature vectors that have a projection greater than or equal to the threshold are assigned to a right child node. The above two steps are then repeated for each child node until the data at a node falls below a predetermined threshold and the node is classified as a terminal node (leaf of the decision tree). After all non-terminal nodes have been processed, the final step is to store a class distribution associated with each terminal node. The class probabilities for a particular feature vector can then be obtained by traversing the decision tree in a top-down fashion until a terminal node is identified which corresponds to the particular feature vector. The information provided by the decision tree is that, in computing the class probabilities for the particular feature vector, only the small number of classes associated with that particular terminal node need be considered. Alternatively, the required class probabilities can be obtained simply by taking the stored distribution of the terminal node associated with the particular feature vector.
    • 2. 发明授权
    • State-dependent speaker clustering for speaker adaptation
    • 用于说话者适应的状态依赖的扬声器聚类
    • US5787394A
    • 1998-07-28
    • US572223
    • 1995-12-13
    • Lalit Rai BahlPonani GopalakrishnanDavid NahamooMukund Padmanabhan
    • Lalit Rai BahlPonani GopalakrishnanDavid NahamooMukund Padmanabhan
    • G10L15/06G10L5/06
    • G10L15/07G10L2015/0631
    • A system and method for adaptation of a speaker independent speech recognition system for use by a particular user. The system and method gather acoustic characterization data from a test speaker and compare the data with acoustic characterization data generated for a plurality of training speakers. A match score is computed between the test speaker's acoustic characterization for a particular acoustic subspace and each training speaker's acoustic characterization for the same acoustic subspace. The training speakers are ranked for the subspace according to their scores and a new acoustic model is generated for the test speaker based upon the test speaker's acoustic characterization data and the acoustic characterization data of the closest matching training speakers. The process is repeated for each acoustic subspace.
    • 一种适用于特定用户使用的独立于说话者的语音识别系统的系统和方法。 该系统和方法从测试扬声器收集声学表征数据,并将数据与为多个训练说话者生成的声学特征数据进行比较。 在特定声学子空间的测试扬声器的声学特性与相同声学子空间的每个训练说话者的声学特性之间计算匹配分数。 训练演讲者根据其分数对子空间进行排名,并且基于测试讲者的声学表征数据和最接近的匹配训练说话者的声学表征数据为测试说话者生成新的声学模型。 对于每个声学子空间重复该过程。
    • 5. 发明授权
    • Specific task composite acoustic models
    • 具体任务复合声学模型
    • US06260014B1
    • 2001-07-10
    • US09153222
    • 1998-09-14
    • Lalit Rai BahlDavid LubenskyMukund PadmanabhanSalim Roukos
    • Lalit Rai BahlDavid LubenskyMukund PadmanabhanSalim Roukos
    • G10L1504
    • G10L15/26G10L15/22G10L2015/223G10L2015/228
    • A method for recognizing speech includes the steps of providing a generic model having a baseform representation of a vocabulary of words, identifying a subset of words relating to an application, constructing a task specific model for the subset of words, constructing a composite model by combining the generic and task specific models and modifying the baseform representation of the subset of words such that the subset of words are recognized by the task specific model. A system for recognizing speech includes a composite model having a generic model having a generic baseform representation of a vocabulary of words and a task specific model for recognizing a subset of words relating to an application wherein the subset of words are recognized using a modified baseform representation. A recognizer compares words input thereto with the generic model for words other than the subset of words and with the task specific model for the subset of words.
    • 一种用于识别语音的方法包括以下步骤:提供具有词汇词典的基本形式表示的通用模型,识别与应用有关的单词的子集,为所述单词子集构建任务特定模型,通过组合来构建复合模型 通用和任务特定模型,并修改单词子集的基本形式表示,使得单词的子集由任务特定模型识别。 用于识别语音的系统包括具有通用模型的复合模型,所述通用模型具有词汇词典的通用基本形式表示,以及用于识别与应用有关的词组的任务特定模型,其中使用经修改的基本形式表示来识别单词的子集 。 识别器将输入的词与除单词子集之外的单词的通用模型和词语子集的任务特定模型进行比较。
    • 6. 发明授权
    • Apparatus and method for performing model estimation utilizing a
discriminant measure
    • 使用判别式进行模型估计的装置和方法
    • US5970239A
    • 1999-10-19
    • US908120
    • 1997-08-11
    • Lalit Rai BahlMukund Padmanabhan
    • Lalit Rai BahlMukund Padmanabhan
    • G06F9/455
    • G10L15/063G10L15/065G10L15/14G10L2015/025
    • Method for performing acoustic model estimation to optimize classification accuracy on speaker derived feature vectors with respect to a plurality of classes corresponding to phones to which a plurality of acoustic models respectively correspond comprises: (a) initializing an acoustic model for each phone; (b) evaluating the merit of the acoustic model initialized for each phone utilizing an objective function having a two component discriminant measure capable of characterizing each phone whereby a first component is defined as a probability that the model for the phone assigns to feature vectors from the phone and a second component is defined as a probability that the model for the phone assigns to feature vectors from other phones; (c) adapting the model for selected phones so as to increase the first component for the phone or decrease the second component for the phone, the adapting step yielding a new model for each selected phone; (d) evaluating the merit of the new models for each phone adapted in step (c) utilizing the two component measure; (e) comparing results of the evaluation of step (b) with results of the evaluation of step (d) for each phone, and if the first component has increased or the second component has decreased, the new model is kept for that phone, else the model originally initialized is kept; (f) estimating parameters associated with each model kept for each phone in order to optimize the function; and (g) evaluating termination criterion to determine if the parameters of the models are optimized.
    • 用于执行声学模型估计以优化关于与多个声学模型分别对应的电话相对应的多个类别的扬声器导出特征向量的分类精度的方法包括:(a)初始化每个电话的声学模型; (b)使用具有能够表征每个电话的双分量判别式度量的目标函数来评估对于每个电话初始化的声学模型的优点,由此第一分量被定义为电话模型分配来自所述电话的特征向量的概率 电话和第二组件被定义为电话模型从其他电话分配给特征向量的概率; (c)使所选择的手机的模型适配,以便增加电话的第一组件或减少电话的第二组件,适应步骤为每个所选择的电话产生新的模型; (d)利用两部分措施评估在步骤(c)中适应的每个电话的新模型的优点; (e)将步骤(b)的评价结果​​与每个电话的步骤(d)的评估结果进行比较,如果第一组分增加或第二组分减少,则为该电话保留新模型, 否则原始初始化的模型被保留; (f)估计与为每个电话保留的每个模型相关的参数,以优化功能; 和(g)评估终止标准以确定模型的参数是否被优化。
    • 7. 发明授权
    • Apparatus for compression coding using cross-array correlation between
two-dimensional matrices derived from two-valued digital images
    • 使用从二值数字图像导出的二维矩阵之间的交叉阵列相关的压缩编码装置
    • US4028731A
    • 1977-06-07
    • US617906
    • 1975-09-29
    • Ronald Barthold ArpsLalit Rai BahlArnold Weinberger
    • Ronald Barthold ArpsLalit Rai BahlArnold Weinberger
    • H03M7/00G06T9/00H03M7/30H04B1/66H04N1/417H04N7/32H04N7/12
    • G06T9/005G06T9/004H04N1/417
    • An apparatus is disclosed for compressing a p .times. q image array of two-valued (black/white) sample points. The image array points are serially applied to the apparatus in consecutive raster scan lines. In response, the apparatus simultaneously forms two matrices respectively representing a high order p .times. q predictive error array and a p .times. q array of location events (such as the raster leading edges of all objects in the image). Improved compression is achieved by selecting between the more compression efficient of two methods for encoding the position of errors in the prediction error array. These alternative methods are conventional run-length coding and a novel form of reference encoding, used selectively but to significant advantage. Thus, a run-length compression codeword is formed from the count C of non-errors between consecutive errors (in response to the occurrence of each error in the jth bit position of the ith scan line of the predictive error array) upon either C.ltoreq.T, where T is a threshold, or C>T and there being no occurrence of a line difference encoding for the error (where i, j, C and T have positive integers). A line difference codeword with difference value v is generated upon the joint event of C>T and either the single or multiple occurrence of location events in the ith-1 scan line of the location event array within the bit position range of B.ltoreq.r.ltoreq.(j+n), where positive integer B is the greater of function D(T,v) and (j-n), and the number of intervening location events, s, within the bit position range of D(T,v).ltoreq.q
    • 公开了用于压缩二值(黑/白)采样点的p×q图像阵列的装置。 图像阵列点在连续的光栅扫描线中串行地应用于设备。 作为响应,装置同时形成分别表示高阶p×q预测误差阵列和位置事件的p×q阵列(诸如图像中的所有对象的光栅前沿)的两个矩阵。 通过在预测误差阵列中编码错误位置的两种方法的更高的压缩效率之间进行选择来实现改进的压缩。 这些替代方法是常规的游程长度编码和一种新颖的参考编码形式,其选择性使用,但具有显着的优点。 因此,从C连续错误之间的非错误的计数C(响应于预测误差阵列的第i个扫描线的第j位位置中的每个错误的出现)而形成游程长度压缩码字, / = T,其中T是阈值,或C> T,并且不存在用于错误的行差编码(其中i,j,C和T具有正整数)。 在C> T的联合事件处产生具有差值v的线差码字,并且在位置事件阵列的位置事件阵列的位置事件阵列的单个或多个位置事件中的单个或多个发生位置位置范围B < 其中正整数B是函数D(T,v)和(jn)中的较大者,D(T,V)和(jn)的位位置范围内的中间位置事件数s v)
    • 9. 发明授权
    • Method and apparatus for a time-synchronous tree-based search strategy
    • 一种基于时间同步树的搜索策略的方法和装置
    • US5884259A
    • 1999-03-16
    • US798011
    • 1997-02-12
    • Lalit Rai BahlEllen Marie Eide
    • Lalit Rai BahlEllen Marie Eide
    • G10L15/08G10L9/06
    • G10L15/08
    • A method and apparatus for using a tree structure to constrain a time-synchronous, fast search for candidate words in an acoustic stream is described. A minimum stay of three frames in each graph node visited is imposed by allowing transitions only every third frame. This constraint enables the simplest possible Markov model for each phoneme while enforcing the desired minimum duration. The fast, time-synchronous search for likely words is done for an entire sentence/utterance. The list of hypotheses beginning at each time frame is stored for providing, on-demand, lists of contender/candidate words to the asynchronous, detailed match phase of decoding.
    • 描述了使用树结构约束声流中的候选词的时间同步,快速搜索的方法和装置。 在每个图形节点访问的最小停留时间为3帧,只允许每三帧进行一次转换。 这个约束使每个音素的最可能的马可夫模型成为可能,同时执行所需的最小持续时间。 快速,时间同步的搜索可能的单词是为整个句子/话语完成的。 存储在每个时间帧开始的假设列表,用于将竞争者/候选词的按需提供到解码的异步,详细匹配阶段。