156results about How to "Reduce recognition" patented technology

Methods and apparatuses are provided for facilitating gesture recognition. A method may include constructing a matrix based at least in part on an input gesture and a template gesture. The method may further include determining whether a relationship determined based at least in part on the constructed matrix satisfies a predefined threshold. In an instance in which the relationship does not satisfy the predefined threshold, the method may also include eliminating the template gesture from further consideration for recognition of the input gesture. In an instance in which the relationship satisfies the predefined threshold, the method may further include determining a rotation matrix based at least in part on the constructed matrix. Corresponding apparatuses are also provided.

Embodiments of the present invention provide a communication fraud identification method and system. The method includes: obtaining a real-time bill, where the real-time bill includes at least a calling number and a called number; if it is determined that the calling number meets a preset condition, obtaining user behavior data related to the called number within a preset time, where the user behavior data includes at least communication data, base station data, signaling data, and service data that are related to the called number; generating a user behavior vector of the called number according to the user behavior data; determining a judgment model corresponding to the user behavior vector in a preset judgment model pool according to the user behavior vector; and determining whether a call corresponding to the real-time bill is a fraudulent call according to the judgment model. In embodiments of the present invention, the real-time bill is identified by using the user behavior datarelated to the called number within the preset time, so that identification of the fraudulent number that appears for the first time or only once is implemented, and time validity of communication fraud identification is improved.

A speech processing system has an arbitrary number of speech recognition modules (Ei, i=1 . . . n) and speech output modules (Aj, j−1 . . . m). The modules provided respectively for a particular type of speech recognition or, respectively, speech output are selected and activated and parameterized according to the situation of application, dependent on an input signal (ES), by a device (MA) for selecting the modules, so that the selected modules are applied for speech recognition or, respectively, speech output corresponding to their construction.

The present invention relates to computer-implemented methods for finding patterns in patterns in a set of k-sequences of symbols (where k≧2) and to a computer readable medium having instructions for controlling a computer system to perform the methods. Patterns of symbols common to each 2-tuple of sequences are identified. Each identified pattern of symbols is represented by a position index binary array (PIBA) which is a set of binary digits. The binary digit in each place in the array that corresponds to a location in a selected reference sequence of a symbol in the identified pattern has a first predetermined binary value. All of the other binary digits in the array have a second predetermined binary value. The position index binary array (PIBA) representations of patterns of each tuple at any order “n” may be combined with the PIBA pattern representations of all other tuples at that same order “n” or with the pattern representations in any selected m-tuple, where m may have any integer value from 2 to (n−1). The patterns of the resulting tuple are identified from the position index binary arrays (PIBAs) produced by the intersection of the set of binary digits in each position index binary array (PIBA) in the n-tuple with the set of binary digits in each position index binary array (PIBA) in the other tuple. The intersections are accomplished logically, as by performing a logical AND operation in a bit-by-bit manner on the binary arrays. Using the places in the position index binary array (PIBA) produced by the intersections having the first predetermined binary value as a guide, the symbols in corresponding locations in the reference sequence are identified. These symbols comprise the symbols in the identified pattern in the resulting tuple.