Abstract:
A totally self-checking memory cell array apparatus (30) has an array (31) of memory cells (32) selectively addressed by row and column decoders (33, 35) which receive unidirectional error detecting code signals as address inputs (34, 36). Data, as a multiple bit data word (A, B, C.sub.1, C.sub.2), is stored in the array (31) in unidirectional error detecting code form. Cells in each row (1-8) of the array have two separate row select connection lines (45 and 45a) for coupling the cell to data and data complement (46, 46*) connections. Error detection circuits (44, 47) are provided which determine errors by comparing the data and data complement lines for each data bit read out of the array and for detecting when multiple bit data words read out of the array are not coded in a unidirectional error detecting code format. The above apparatus provides error indications in case of any unidirectional errors in the row or column input address signals or the row or column decoders, or any unidirectional error corruption of the data stored in the memory cell array. This is achieved without completely duplicating each memory cell in the array and all row and column decoder circuitry.
Abstract:
In a speech synthesis technique used in a network (110, 115), a set of text words is accepted by a speech engine software function (210) in a client device (105). From the set of text words, an invalid subset of text words is determined for which the text words are not in a word synthesis dictionary of the client device. The invalid subset of text words is transmitted over the network to a server device (120), which generates a set of word pronunciations including at least a portion of the text words of the invalid subset of text words and pronunciations associated with each of the text words. The client device uses the pronunciations for speech synthesis and may store them in a local word synthesis dictionary (220) stored in a memory (150) of the client device.
Abstract:
The present invention teaches a method (400), device and system (300) utilizing at least one of: mapping a sequence of phones to a sequence of articulatory features and utilizing prominence and boundary information, in addition to a predetermined set of rules for type, phonetic context, syntactic and prosodic context for phones to provide provide a system that generates segment durations efficiently with a small training set.
Abstract:
A method (400), device and system (300) provide, in response to linguistic information, efficient generation of a parametric representation of speech using a neural network. The method provides, in response to linguistic information efficient generation of a refined parametric representation of speech, comprising the steps of: A) using a data selection module to retrieve representative parameter vectors for each segment description according to the phonetic segment type and the phonetic segment types included in adjacent segment descriptions; B) interpolating between the representative parameter vectors according to the segment descriptions and duration to provide interpolated statistical parameters; C) converting the interpolated statistical parameters and linguistic information to neural network input parameters; D) utilizing a statistically enhanced neural network/neural network with post-processor to provide neural network output parameters that correspond to a parametric representation of speech; and converting the neural network output parameters to a refined parametric representation of speech.