Abstract: A system is provided configured to control routing of incoming customer calls to agent devices over a routing system, comprising: a processor and a non-transitory computer readable medium comprising a plurality of instructions, where the plurality of instructions comprises: instructions that, when executed, determine respective performance indicators (PIs) to associate with multiple respective agents in response to a received call; and instructions that, when executed, select a respective agent to handle the received call at least based in part upon the determined respective PIs.

Abstract: A computing system is provided that includes a runtime (RT) controller that produces a corresponding sequence of individual RT prediction results. A FIFO buffer organizes RT confidence score values into RT confidence score value frames. An RT storage circuit stores RT confidence values in an RT value histogram structure that indicates frequency of occurrence of individual RT confidence score values. A training controller produces training prediction results. A training storage circuit stores training confidence values in a training value histogram structure that indicates frequency of occurrence of training confidence score values. A comparison circuit compares RT confidence values with training confidence values in the training value histogram structure. A calibration controller circuit produces a calibration update signal based upon the comparison.

Abstract: A computing system comprising: a runtime controller to produce a corresponding sequence of individual RT prediction results; a FIFO buffer to organize RT confidence score values into RT confidence score value frames; an RT storage circuit to store RT confidence values in an RT value histogram structure that indicates frequency of occurrence of individual RT confidence score values; a training controller to produce training prediction results; a training storage circuit to store training confidence values in a training value histogram structure that indicates frequency of occurrence of training confidence score values; a comparison circuit to compare RT confidence values with training confidence values in the training value histogram structure; a calibration controller circuit to produce a calibration update signal based upon the comparison.

Abstract: A method of creating a decision tree to enable a character recognition device to recognize characters in a new unknown font includes scanning a document printed in the unknown font to generate an array of pixels, with each pixel having a neighborhood state based on the colors of the surrounding pixels. A plurality of clusters of pixels, each representing a printed character, are identified. A pixel in one cluster is selected, and its neighborhood state determined. The neighborhood state is used to address a memory that has stored in it a probability table providing the probability, in a second font different from the new font being taught, that a pixel is black as a function of its neighborhood state. The stored probability of black associated with the neighborhood state of the select pixel is read from the memory and assigned as the probability of the selected pixel. The decision tree for the new font is generated using that assigned probability of black.

Abstract: Method and apparatus which cyclically generate a compressed, arithmetically-coded binary stream in response to binary occurrence counts of symbols in an uncoded string. The symbols in the uncoded string are drawn from a multi-character alphabet which is not necessarily a binary one. Coding operations and hardware are simplified by deriving from the binary occurrence counts an estimate of the probability of each unencoded symbol at its precise lexical location. The probability estimation eliminates any requirement for division or multiplication by employing magnitude-shifting of the binary occurrence counts. The encoded stream is augmented by the estimated symbol probability at the same time that an internal variable is updated with an estimate of the portion of a probability interval remaining after coding the current symbol, the interval estimate being obtained from the left-shifted occurrence counts. Decoding is the dual of encoding.