Abstract: Methods, systems, and products are disclosed for administering a personal interactive voice response service. A personalized greeting is retrieved that is associated with a calling party and with a called party. The calling party's response to the greeting is received, and stored information is retrieved that is associated with the calling party's response and with the called party. The stored information is presented to the calling party.

Abstract: In a method of producing a scalable data stream of at least two blocks of output data of a first coder and a block of output data of a second coder, wherein the at least two blocks of output data of the first coder together represent a current section of an input signal in the first coder, and wherein the block of output data of the second coder represents the same current section of the input signal, a determination data block for the current section of the input signal is written. In addition, the block of output data of the second coder, in the direction of transfer from a coding device to a decoding device, is written after the determination data block for the current section of the input signal.

Abstract: A method of presenting a multi-modal help dialog move to a user in a multi-modal dialog system is disclosed. The method comprises presenting an audio portion of the multi-modal help dialog move that explains available ways of user inquiry and presenting a corresponding graphical action performed on a user interface associated with the audio portion. The multi-modal help dialog move is context-sensitive and uses current display information and dialog contextual information to present a multi-modal help move that is currently related to the user. A user request or a problematic dialog detection module may trigger the multi-modal help move.

Abstract: A voice-enabled help desk service is disclosed. The service comprises an automatic speech recognition module for recognizing speech from a user, a spoken language understanding module for understanding the output from the automatic speech recognition module, a dialog management module for generating a response to speech from the user, a natural voices text-to-speech synthesis module for synthesizing speech to generate the response to the user, and a frequently asked questions module. The frequently asked questions module handles frequently asked questions from the user by changing voices and providing predetermined prompts to answer the frequently asked question.

Abstract: The emotion is to be added to the synthesized speech as the prosodic feature of the language is maintained. In a speech synthesis device 200, a language processor 201 generates a string of pronunciation marks from the text, and a prosodic data generating unit 202 creates prosodic data, expressing the time duration, pitch, sound volume or the like parameters of phonemes, based on the string of pronunciation marks. A constraint information generating unit 203 is fed with the prosodic data and with the string of pronunciation marks to generate the constraint information which limits the changes in the parameters to add the so generated constraint information to the prosodic data. A emotion filter 204, fed with the prosodic data, to which has been added the constraint information, changes the parameters of the prosodic data, within the constraint, responsive to the feeling state information, imparted to it.

Abstract: A spoken dialog system and method having a dialog management module are disclosed. The dialog management module includes a plurality of dialog motivators for handling various operations during a spoken dialog. The dialog motivators comprise an error handling, disambiguation, assumption, confirmation, missing information, and continuation. The spoken dialog system uses the assumption dialog motivator in either a-priori or a-posteriori modes. A-priori assumption is based on predefined requirements for the call flow and a-posteriori assumption can work with the confirmation dialog motivator to assume the content of received user input and confirm received user input.

Abstract: A context-free grammar can be represented by a weighted finite-state transducer. This representation can be used to efficiently compile that grammar into a weighted finite-state automaton that accepts the strings allowed by the grammar with the corresponding weights. The rules of a context-free grammar are input. A finite-state automaton is generated from the input rules. Strongly connected components of the finite-state automaton are identified. An automaton is generated for each strongly connected component. A topology that defines a number of states, and that uses active ones of the non-terminal symbols of the context-free grammar as the labels between those states, is defined. The topology is expanded by replacing a transition, and its beginning and end states, with the automaton that includes, as a state, the symbol used as the label on that transition. The topology can be fully expanded or dynamically expanded as required to recognize a particular input string.

Abstract: A computer-parsing system using vectors (lists) to represent natural-language elements, providing a robust, distributed way to score grammaticality of an input string by using as a source material a large corpus of natural-language text. The system uses recombining of asymmetric associations of syntactically similar strings to form the vectors. The system uses equivalence lists for subparts of the string to build equivalence lists for longer strings in an order controlled by the potential parse to be scored. The power of recombination of vector elements in building longer strings provides a means of representing collocational complexity. Grammaticality scoring is based upon the number and similarity of the vector elements.

Abstract: A user interface, and associated techniques, that permit a fast and efficient way of correcting speech recognition errors, or of diminishing their impact. The user may correct mistakes in a natural way, essentially by repeating the information that was incorrectly recognized previously. Such a mechanism closely approximates what human-to-human dialogue would be in similar circumstances. Such a system fully takes advantage of all the information provided by the user, and on its own estimates the quality of the recognition in order to determine the correct sequence of words in the fewest number of steps.

Abstract: A method and structure for automatically producing bridging inferences that join two related input sentences, by applying a lexicon and ontology data structure to a first input sentence to produce first input tagged sentences, applying the lexicon and ontology data structure to a second input sentence to produce second input tagged sentences, matching each first input tagged sentence to first rules, generating first inferred tagged sentences from the first rules, matching the first inferred tagged sentences to second rules, generating second inferred tagged sentences from the second rules, matching the second inferred tagged sentences to third rules, generating third inferred tagged sentences from the third rules, and so on, until a final inferred tagged sentence matches any second input tagged sentence.

Abstract: The operation of a device by a user is detected, and one or more speech input executing commands corresponding to the operated device are provided to the user, e.g., by speech or by being displayed on a screen. Speech input guidance may be stopped if it would interfere with an audio or image output of an operated device, or if a count of guidance speech outputs exceeds a predetermined number.

Abstract: An orthographic anchor for each word in a dictionary is created in an orthographic space by mapping the words and a set of letter patterns characteristic of the words into the orthographic space. In one aspect the orthographic anchors are row or column vectors resulting from a decomposition of a matrix of feature vectors created by the mapping. In another aspect, a pronunciation for an input word is modeled based on a set of candidate phoneme strings that have pronunciations close to the input word in the orthographic space.

Abstract: A system analyzes text, determines phrasing and, in an exemplary embodiment, reformats the text to establish optimal spacing and related features for readability, reader comprehension and publishing economies. A neural network uses a library of text data to analyze text and determine phrases. Formatting emphasizes phrases using one or more of a plurality of techniques including word spacing, text darkness and controlling line breaks.

Abstract: A system for understanding entries, such as speech, develops a classifier by employing prior knowledge with which a given corpus of training entries is enlarged threefold. A rule is created for each of the labels employed in the classifier, and the created rules are applied to the given corpus to create a corpus of attachments by appending a weight of ?p(x), or 1??p(x), to labels of entries that meet, or fail to meet, respectively, conditions of the labels' rules, and to also create a corpus of non-attachments by appending a weight of 1??p(x), or ?p(x), to labels of entries that meet, or fail to meet conditions of the labels' rules.

Abstract: A speech recognition system uses a phoneme counter to determine the length of a word to be recognized. The result is used to split a lexicon into one or more sub-lexicons containing only words which have the same or similar length to that of the word to be recognized, so restricting the search space significantly. In another aspect, a phoneme counter is used to estimate the number of phonemes in a word so that a transition bias can be calculated. This bias is applied to the transition probabilities between phoneme models in an HNN based recognizer to improve recognition performance for relatively short or long words.

Abstract: In this navigation apparatus, when speech recognition of inputted speech is carried out, keywords included in the content of the recognized speech are searched from a dictionary DB, and then these words are displayed as keywords of a POI search. When a correction of a keyword is required by the user, because most errors occur in the first phonetic symbol of the misrecognized word, a search of words each having phonetic symbols in which the first phonetic symbol of the misrecognized word is changed from the phonetic symbols of the word to be corrected (i.e., a search of words having one different first phonetic symbol) is carried out to present candidates for correction. In this navigation apparatus, because the displayed candidates for correction are limited to words having a different first phonetic symbol which has a high possibility of being the cause of misrecognition, the user can correct the misrecognized keyword by a simple operation.

Abstract: A phonetic system having vowel phonetic symbols separated into full sound symbols and half sound symbols, and consonant phonetic symbols. The full sounds symbols are represented by letters in the English alphabet. The half sound symbols are represented by letters in the English alphabet with a predetermined symbol. Most consonant phonetic symbols are taken from consonant letters of English vocabularies. A phonetic diagram where the vowel phonetic symbols and the consonant phonetic symbols are systematically arranged therein is provided to allow user to easily visualize the vowel and consonant phonetic symbols. The phonetics utilizes direct phonetic spelling method, so as to enable easier obtaining of correct pronunciation. It also helps avoiding the possibility of misreading by utilizing combination of letters that do not appear in the English language.

Abstract: Context-free grammars generally comprise a large number of rules, where each rule defines how a sting of symbols is generated from a different series of symbols. While techniques for creating finite-state automata from the rules of context-free grammars exist, these techniques require an input grammar to be strongly regular. Systems and methods that convert the rules of a context-free grammar into a strongly regular grammar include transforming each input rule into a set of output rules that approximate the input rule. The output rules are all right- or left-linear and are strongly regular. In various exemplary embodiments, the output rules are output in a specific format that specifies, for each rule, the left-hand non-terminal symbol, a single right-hand non-terminal symbol, and zero, one or more terminal symbols. If the input context-free grammar rule is weighted, the weight of that rule is distributed and assigned to the output rules.

Abstract: A method for creating a language model from a task-independent corpus is provided. In one embodiment, a task dependent unified language model is created. The unified language model includes a plurality of context-free grammars having non-terminals and a hybrid N-gram model having at least some of the same non-terminals embedded therein.

Abstract: A method and apparatus for noise suppression is described herein. The channel gain is controlled based on a degree of variability of the background noise. The noise variability estimate is used in conjunction with a variable attenuation concept to produce a family of gain curves that are adaptively suited for a variety of combinations of long-term peak SNR and noise variability. More specifically, a measure of the variability of the background noise is used to provide an optimized threshold that reduces the occurrence of non-stationary background noise entering into the transition region of the gain curve.