1223 results about "Best matching" patented technology

The invention provides a speech recognition method for selecting a combination of list elements via a speech input, wherein a first list element of the combination is part of a first set of list elements and a second list element of the combination is part of a second set of list elements, the method comprising the steps of receiving the speech input, comparing each list element of the first set with the speech input to obtain a first candidate list of best matching list elements, processing the second set using the first candidate list to obtain a subset of the second set, comparing each list element of the subset of the second set with the speech input to obtain a second candidate list of best matching list elements, and selecting a combination of list elements using the first and the second candidate list.

The present invention provides a data-structure to store a search database and provides techniques to build this datastructure given a list of prefixes (P) and to search this database efficiently for a best matching prefix for an address D. The data-structure can be stored in standard memory (14), where values are stored associated with memory address locations. The data structure includes representations of addressable linked tables (FIG. 3b). The representations are related to a binary search trie (FIG. 1) and each linked table (T) has at least one entry. Entries in a table span more than one level of the binary search trie. The spanning feature relates to compression of a binary search trie into a finite number of levels (and hence tables). The finite number is less than the number of levels in the binary search trie. Hence the search algorithm is restricted to a finite, and predetermined number of search accesses to the tables to obtain a best-match result.

Methods and systems are disclosed for routing callers to agents in a contact center, along with an intelligent routing system. A method for routing callers includes routing a caller, if agents are available, to an agent based on a pattern matching algorithm (which may include performance based matching, pattern matching based on agent and caller data, computer models for predicting outcomes of agent-caller pairs, and so on). Further, if no agents are available for the incoming caller, the method includes holding the caller in a shadow queue, e.g., a set of callers. When an agent becomes available the method includes scanning all of the callers in the shadow queue and matching the agent to the best matching caller within shadow queue.

Systems and methods are disclosed for routing callers to agents in a contact center, along with an intelligent routing system. An exemplary interface for use with a contact center includes a graphical user element for adjusting a time limit for a caller to be held before routed to an agent according to a pattern matching algorithm where the caller is compared to a set of agents via the pattern matching algorithm and routed to the best matching agent of the set of agents if available prior to the time limit and routed to the best matching agent of available agents if the time limit is exceeded. The interface may further display an estimated effect of the time limit on at least one outcome variable, which may include revenue generation, cost, customer satisfaction, first call resolution, cancellation, or other variable outputs from the pattern matching algorithm(s) of the system.

A system and method is provided for recognizing a speech input and selecting an entry from a list of entries. The method includes recognizing a speech input. A fragment list of fragmented entries is provided and compared to the recognized speech input to generate a candidate list of best matching entries based on the comparison result. The system includes a speech recognition module, and a data base for storing the list of entries and the fragmented list. The speech recognition module may obtain the fragmented list from the data base and store a candidate list of best matching entries in memory. A display may also be provided to allow the user to select from a list of best matching entries.

This invention provides a computer system architecture and method for providing the same which can include a web page search node including a web page collection. The system and method can also include a web server configured to receive, from a given user via a web browser, a search query including keywords. The node is caused to search pages in its own collection that best match the search query. A search page returner may be provided which is configured to return, to the user, high ranked pages. The node may include a power-efficiency-enhanced processing subsystem, which includes M processors. The M processors are configured to emulate N virtual processors, and they are configured to limit a virtual processor memory access rate at which each of the N virtual processors accesses memory. The memory accessed by each of the N virtual processors may be RAM. In select embodiments, the memory accessed by each of the N virtual processors includes DRAM having a high capacity yet lower power consumption then SRAM.

Motion estimation is the science of predicting the current frame in a video sequence from the past frame (or frames), by slicing it into rectangular blocks of pixels, and matching these to past such blocks. The displacement in the spatial position of the block in the current frame with respect to the past frame is called the motion vector. This method of temporally decorrelating the video sequence by finding the best matching blocks from past reference frames—motion estimation—makes up about 80% or more of the computation in a video encoder. That is, it is enormously expensive, and methods do so that are efficient are in high demand. Thus the field of motion estimation within video coding is rich in the breadth and diversity of approaches that have been put forward. Yet it is often the simplest methods that are the most effective. So it is in this case. While it is well-known that a full search over all possible positions within a fixed window is an optimal method in terms of performance, it is generally prohibitive in computation. In this patent disclosure, we define an efficient, new method of searching only a very sparse subset of possible displacement positions (or motion vectors) among all possible ones, to see if we can get a good enough match, and terminate early. This set of sparse subset of motion vectors is preselected, using a priori knowledge and extensive testing on video sequences, so that these “predictors” for the motion vector are essentially magic. The art of this method is the preselection of excellent sparse subsets of vectors, the smart thresholds for acceptance or rejection, and even in the order of the testing prior to decision.

The invention relates to methods and apparatus for matching a query data object with a candidate data object by esetracting and comparing fingerprints of said data objects. In an embodiment of the invention apparatus comprising a fingerprint extraction module (110), a fingerprint matching module (210), a statistical module (120) and an identification module is provided. The fingerprint extraction module (110) receives an information signal forming part of a query object and constructs a query fingerprint. The fingerprint matching module (210) compares the query fingerprint to candidates stored in a database (215) to find at least on potentially best matching candidate. Meanwhile, the statistical module determines a statistical model of the query fingerprint so as to, for instance, determine the statistical distribution of certain information inside the query fingerprint. The threshold determiner (120) is arranged, on the basis of the distribution of the query fingerprint to derive an adaptive threshold distance within which the query fingerprint and a potentially best matching candidate may be declared similar by the identification module (130). By setting a threshold which may depend on statistical data derived from the query and / or candidate fingerprint, an improved false acceptance rate F.A.R. may be achieved.

Systems and methods are disclosed for a server generating a plurality of proxy prediction models for each of a plurality of applications for use by client devices. Providing a prediction model based on a data distribution that more closely matches the user private data of the actual user of the client device, as opposed to a generic model, can improve the accuracy of predictions and improve the benefits to the user of the client device. The plurality of prediction models are generated by a server and provided to a plurality of clients. For a particular application, a client device can use previously collected private user data to select one of the plurality of prediction models for the application as being a closest matching prediction model to use for a particular user.

An image management method and system provides for storing, indexing, searching and / or retrieving image data. The content of an image collection is pre-processed to identify stable and repeatable keypoints for each image in the collection. Fingerprint information is computed from local groups of keypoints, and the resulting fingerprint information is stored in a compact fingerprint database. The computing of the fingerprint information is based on combinations of a subgroup of the strongest keypoints in an image, called anchor keypoints, in addition to a number of non-anchor keypoints. For each fingerprint in the compact fingerprint database, a sequence of candidate fingerprint combinations is generated and stored in a Fan Tree and / or hashtable and a corresponding fingerprint data structure. The sequence of fingerprint combinations allows several non-anchor keypoints to be missing, while still allowing the system and method to correctly detect fingerprints with high accuracy. A realtime image query is performed by identifying keypoints and computing fingerprints from the query image and matching the query fingerprints to the existing Fan Tree and / or hashtable fingerprint data to determine the best matching image or set of images within the collection. At least one target image is retrieved based on the determining operation, and the retrieved target image is displayed, printed, stored and / or transmitted.

A motion estimation and compensation device that avoids discrepancies in chrominance components which could be introduced in the process of motion vector estimation. The device has a motion vector estimator for finding motion vectors in given interlace-scanning chrominance-subsampled video signals. The estimator compares each candidate block in a reference picture with a target block in an original picture by using a sum of absolute differences (SAD) in luminance as similarity metric, chooses a best matching candidate block that minimizes the SAD, and determines its displacement relative to the target block. In this process, the estimator gives the SAD of each candidate block an offset determined from the vertical component of a corresponding motion vector, so as to avoid chrominance discrepancies. A motion compensator then produces a predicted picture using such motion vectors and calculates prediction error by subtracting the predicted picture from the original picture.

A mosaic image resembling a target image is composed of images from a data base. The target image is divided into regions of a specified size and shape, and the individual images from the data base are compared to each region to find the best matching tile. The comparison is performed by calculating a figure of visual difference between each tile and each region. The data base of tile images is created from raw source images using digital image processing, whereby multiple instances of each individual raw source image are produced. The tile images are organized by subject matter, and tile matching is performed such that all required subject matters are represented in the final mosaic. The digital image processing involves the adjustment of colour, brightness and contrast of tile images, as well as cropping. An image description index locates each image in the final mosaic.

A system that automatically matches schema elements is provided. In one aspect, given a selected element of one schema, the system can calculate the best matching candidate elements of another schema. The calculation can be based on a heuristic combination of factors, such as element names, element types, schema structure, existing matches, and the history of actions taken by the user. Accordingly, the best candidate (according to the calculation) can be emphasized and / or highlighted. The tool can auto-scroll to the best choice. Similarly, the user can request the calculation and display to best candidates by pressing a keyboard key or hot key. As well, the user can prompt display of the best candidates by using the mouse (e.g., moving the mouse over the element E or clicking on E), or both (e.g., mouse over with hot key depressed).

The present invention is a system and method to enable advertisement subsidized telecommunications services, which can deliver a campaign comprised of multiple advertisements, each advertisement using a different format (text, audio and video), to user's different terminals (cell phone, soft phone, PDA, PC, etc.) by using different telecommunications channels (text message, phone call, multimedia message, ring tone) simultaneously. The system is comprised of three layers: a campaign manager to manage campaign state, a service logic, which determines the user population and the channel best matching each advertisement's content and format, and a channel manager which emulates a confederation of service applications to simultaneously tap into various telecommunications channels through a Service Delivery Platform (SDP), or by directly attaching to the operator's network.

Embodiments of a dialog system employing a discriminative action selection solution based on a trainable machine action model. The discriminative machine action selection solution includes a training stage that builds the discriminative model-based policy and a decoding stage that uses the discriminative model-based policy to predict the machine action that best matches the dialog state. Data from an existing dialog session is annotated with a dialog state and an action assigned to the dialog state. The labeled data is used to train the discriminative model-based policy. The discriminative model-based policy becomes the policy for the dialog system used to select the machine action for a given dialog state.

The invention relates to a system and method for recognition, classification and spatial localization of bounded 3D-objects. In particular it relates to a computerized method for recognition, classification and localization of objects. The method comprises generation of a training database based on a large number of training views recorded by a camera or constructed using a CAD representation of an object. Characteristic curves are derived from the training views, and primitives of the curves are detected. Intrinsic and extrinsic descriptors of features are stored in the database together with data about the object class and pose of the view. Finally the recognition takes place in two stages: First the intrinsic descriptors of the recognition view are compared with those of the database. Second, among the best matching features it is explored which features agree mutually in the sense that they suggest the same object class at the same pose.

The invention discloses a self-adapting random resonance weak signal detection method, which achieves the self-adapting detection of weak periodic signal through combining a matching random resonance and an imposed signal induced random resonance. According to the theory of random resonance, firstly, numerical simulation is processed to receive correspondence between the noise intensity and the frequency of the best matching random resonance of a nonlinear bistable system in a range of extremely low frequency and under the condition of small-signal; and a high-frequency weak signal encountered in a project can be processed by using the change of normalized scale. For the detection of a weak signal with extremely low message-to-noise ratio and large noise intensity, the heights of voltage barriers of the bistable system can be changed by using the induced random resonance, thereby helping a weak eigenfrequency signal to fulfill the transition between voltage barriers, so that the bistable system reaches the random resonance state, thereby achieving the self-adapting detection of the weak periodic signal.

In low-voltage circuits, there is often insufficient voltage to use a current source to bias a transconductance amplifier stage. This is particularly true in mixers where a switching circuit must be stacked on top of the transconductance input stage. One way around this problem is to get "double-duty" out of the input differential pair, using it both for gain stage and for DC bias. This is done by AC coupling in a high-frequency input signal, while using a low-frequency, DC-coupled circuit to establish the proper bias level. One common technique is to use a simple current mirror scheme to establish the DC level. Proper biasing using this technique requires good matching of resistance. In some implementations of transconductance amplifiers, particularly those that use inductors as degeneration elements, series resistance of the inductor and interconnect resistance can cause significant errors in the bias current. This invention addresses that problem by using an operational amplifier with a current-sensing resistor and a low-frequency feedback loop to compensate automatically for any resistance errors. The operational amplifier drives the feedback voltage (generated in accordance with the sensed voltage at the current-sensing resistor and applied to one input of the operational amplifier) towards a reference voltage that is applied to the other input of the operational amplifier to bias the transistor(s) in the transconductance amplifier for desired operating conditions.

A network based interactive speech system responds in real-time to speech-based queries addressed to a set of topic entries. A best matching response is provided based on speech recognition processing and natural language processing performed on recognized speech utterances to identify a selected set of phrases related to the set of topic entries. Another routine converts the selected set of phrases into a search query suitable for identifying a first group of one or more topic entries corresponding to the speech-based query. The words / phrases can be assigned different weightings and can include entries which are not actually in the set of topic entries.

Material selection systems and methods for quickly identifying which existing material best matches a desired set of properties are described so that product development time can be minimized. Users may input the properties they desire in a material, which properties they want searched and scored, the acceptable values of those properties, and a priority value for each property. Preliminary matching materials may be retrieved from a materials database, and an index value for each property value may be calculated. One of four fuzzy membership functions may then be utilized to calculate a scored property value for each property of each material. The scored property value may then be weighted to account for the priority value assigned to each property. The results may then be sorted in descending order based on their overall match scores, and output to the user so the best matching material(s) is readily identifiable by the user.

The invention discloses a machine learning-based wireless sensing motion identification method which comprises the following steps: a step of data collection, a step of data denoising operation, a step of feature extraction and a step of SVM model training and identifying operation. During data collection operation, absolute value of a group of CSI data collected on each sampling point is obtained and is read into a 30*Nr*Nt matrix form. A PCA mode is mainly adopted for the data denoising operation. Feature extraction operation can be conducted based on discrete wavelet transformation. To make SVM model training convenient, training samples are subjected to Kmeans clustering operation via the machine learning-based wireless sensing motion identification method, n clustering centers can be used as word bags, and voting operation is performed based on feature vectors and best matching items of all the word bags; when the matrix form feature vectors are converted into column vectors, SVM model training can be realized conveniently. The machine learning-based wireless sensing motion identification method is a human body behavior identification method which is high in identification accuracy and high in robustness for environment change.

A method and system for characterizing features in a source multifeatured three-dimensional object, and for locating a best-matching three-dimensional object from a reference database of such objects by performing a viewpoint invariant search among the reference objects. The invention further includes the creation of a three-dimensional representation of the source object by deforming a reference object.

A three-dimensional helmet display of an augmented reality system is characterized by adopting an optical perspective type structure; being horizontally symmetrical by taking the nose part of a user as a central line; and being provided with an image source, a polarization azimuth adjustment mirror with adjustable azimuth, an optical imaging system and a polarization combination mirror in sequencefrom the external side to the human eye center along the optical axis direction, wherein the polarization combination mirror leads the light direction of the image source to be reflected and deflected by 90 degrees and then enter human eyes; the external light forms a 90-degree angle with the image source light, and then enters human eyes through the transmission of the polarization combination mirror after pass through the polarization mirror with the adjustable azimuth; two images forming a three-dimensional image pair are respectively transmitted to the image sources at the left side and the right side; the polarization azimuth adjustment mirror and the polarization combination mirror constitute an image source brightness adjustment unit; and the polarization mirror and the polarization combination mirror constitute an external light brightness adjustment unit. The invention can lead the virtual environment and the real environment of the three-dimensional helmet display to achievethe best matching state, eliminates the two-eye competition phenomenon, and is used for the augmented reality system.

A method for automatically producing video cartoons with user-provided faces superimposed on cartoon characters is presented. A cartoon template stores the original video cartoon with unanimously-coloured backgrounds and original cartoon characters' faces drawn following the guidelines of the invention. A background detection algorithm is used to detect the unanimously-coloured backgrounds, while a face detection algorithm is used to detect the facial colours, facial expressions, sizes, rotations, positions and clippings of the original cartoon characters' faces. The detected unanimously-coloured backgrounds may be replaced by optional user-provided backgrounds. User-provided faces with the best matching user-specified facial colours and expressions are superimposed over and on top of the corresponding original faces of the cartoon characters at the detected sizes, rotations, positions and clippings to produce the final video cartoon. The cartoon template can be distributed to many different users. Different users can add different user-provided faces, background images and audio to the same cartoon template to produce many different final video cartoons.

The invention discloses a method for recognizing aberrant behaviors based on contours. The method is characterized in that the detection and the tracking of moving targets are primarily performed for the image sequences collected by a camera so as to extract target contours; then spatial information of the moving targets in each frame is indicated by utilizing R transformation; then the spatial information is rearranged and combined as characteristic vectors of behavior analysis and the characteristic dimension reduction is performed by adopting principal component analysis; finally the transformation relation of the contour sequences with spatial information in the time is indicated by utilizing a hidden Markov model, and all the behaviors can be indicated with respective parameters of the hidden Markov model. In the recognition process, the characteristic sequences of new behaviors are compared with the storage parameters, and the behaviors best matched are selected upon the maximum likelihood principle. Therefore, the method for recognizing aberrant behaviors has an important significance of automatic analysis for intelligent visual monitoring, so that time, places and characters of occurrence events in the scene can be known without assistance of the people; moreover, the method for recognizing aberrant behaviors also can be used for video retrieval so as to assist the people to seek for the interesting events in the video frequency.