Abstract: A system identifies a document that includes an address and locates business information in the document. The system assigns a confidence score to the business information, where the confidence score relates to a probability that the business information is associated with the address. The system determines whether to associate the business information with the address based on the assigned confidence score.

Abstract: A speech synthesis system can select recorded speech fragments, or acoustic units, from a large database of acoustic units to produce artificial speech. The selected acoustic units are chosen to minimize a combination of target and concatenation costs for a given sentence. Concatenation costs are expensive to compute. Processing is reduced by pre-computing and caching the concatenation costs. The number of possible sequential pairs of acoustic units makes such caching prohibitive. A method for constructing an efficient concatenation cost database is provided by synthesizing a large body of speech, identifying the acoustic unit sequential pairs generated and their respective concatenation costs, and storing those concatenation costs likely to occur.

Abstract: A QWERTY-based cluster keyboard is disclosed. In the preferred embodiment, the keyboard comprises fourteen alphabet keys arranged such that all the letters in the alphabet are distributed in three rows of keys and in the standard QWERTY positions. Stochastic language models are used to reduce the error rate for typing on the keyboards. The language models consist of probability estimates of occurrences of n-grams (sequences of n consecutive words), wherein n is preferably 1, 2 or 3. A delay parameter d, which is related to the period of time the system displays the predicted intended word upon entry of a word boundary, is preferably zero to immediately display the primary word choice at a word boundary and provide the user the option to select the secondary candidate if necessary. Two disambiguation keys enable the user to identify which letter is intended as a secondary option to the language model predictions.

Abstract: A speech synthesis system can select recorded speech fragments, or acoustic units, from a very large database of acoustic units to produce artificial speech. The selected acoustic units are chosen to minimize a combination of target and concatenation costs for a given sentence. However, as concatenation costs, which are measures of the mismatch between sequential pairs of acoustic units, are expensive to compute, processing can be greatly reduced by pre-computing and caching the concatenation costs. Unfortunately, the number of possible sequential pairs of acoustic units makes such caching prohibitive. However, statistical experiments reveal that while about 85% of the acoustic units are typically used in common speech, less than 1% of the possible sequential pairs of acoustic units occur in practice.

Abstract: A speech synthesis system can select recorded speech fragments, or acoustic units, from a very large database of acoustic units to produce artificial speech. The selected acoustic units are chosen to minimize a combination of target and concatenation costs for a given sentence. However, as concatenation costs, which are measures of the mismatch between sequential pairs of acoustic units, are expensive to compute, processing can be greatly reduced by pre-computing and caching the concatenation costs. Unfortunately, the number of possible sequential pairs of acoustic units makes such caching prohibitive. However, statistical experiments reveal that while about 85% of the acoustic units are typically used in common speech, less than 1% of the possible sequential pairs of acoustic units occur in practice.

Abstract: Systems and methods for identifying the N-best strings of a weighted automaton. A potential for each state of an input automaton to a set of destination states of the input automaton is first determined. Then, the N-best paths are found in the result of an on-the-fly determinization of the input automaton. Only the portion of the input automaton needed to identify the N-best paths is determinized. As the input automaton is determinized, a potential for each new state of the partially determinized automaton is determined and is used in identifying the N-best paths of the determinized automaton, which correspond exactly to the N-best strings of the input automaton.

Abstract: A speech synthesis system can select recorded speech fragments, or acoustic units, from a very large database of acoustic units to produce artificial speech. The selected acoustic units are chosen to minimize a combination of target and concatenation costs for a given sentence. However, as concatenation costs, which are measures of the mismatch between sequential pairs of acoustic units, are expensive to compute, processing can be greatly reduced by pre-computing and caching the concatenation costs. Unfortunately, the number of possible sequential pairs of acoustic units makes such caching prohibitive. However, statistical experiments reveal that while about 85% of the acoustic units are typically used in common speech, less than 1% of the possible sequential pairs of acoustic units occur in practice.

Abstract: A large vocabulary speech recognizer including a combined weighted network of transducers reflecting fully expanded context-dependent modeling of pronunciations and language that can be used with a single-pass Viterbi or other coder based on sequences of labels provided by feature analysis of input speech.

Abstract: A pattern recognition system and method for optimal reduction of redundancy and size of a weighted and labeled graph presents receiving speech signals, converting the speech signals into word sequence, interpreting the word sequences in a graph where the graph is labeled with word sequences and weighted with probabilities and determinizing the graph by removing redundant word sequences. The size of the graph can also be minimized by collapsing some nodes of the graph in a reverse determinizing manner. The graph can further be tested for determinizability to determine if the graph can be determinized. The resulting word sequence in the graph may be shown in a display device so that recognition of speech signals can be demonstrated.

Abstract: A language recognition methodology is provided whereby any finite-state model of context may be used in a very general class of decoding cascades, and without requiring specialized decoders or full network expansion. The methodology includes two fundamental improvements: (1) a simple generalization, weighted finite-state transducers, of existing network models, and (2) a novel on-demand execution technique for network combination. With the methodology of the invention one or more of the network cascades are formulated as a finite state transducer, and is composed, for a selected portion of the network, with a next successively higher level of the network cascade to prescribe a mapped portion of that next successively higher level corresponding to the portion of the network cascade selected to be expanded.

Abstract: A pattern recognition system and method for optimal reduction of redundancy and size of a weighted and labeled graph presents receiving speech signals, converting the speech signals into word sequences, interpreting the word sequences in a graph where the graph is labeled with word sequences and weighted with probabilities and determinizing the graph by removing redundant word sequences. The size of the graph can also be minimized by collapsing some nodes of the graph in a reverse determinizing manner. The graph can further be tested for determinizability to determine if the graph can be determinized. The resulting word sequence in the graph may be shown in a display device so that recognition of speech signals can be demonstrated.

Abstract: The present invention provides a method of expanding a string of one or more digits to form a verbal equivalent using weighted finite state transducers. The method provides a grammatical description that expands the string into a numeric concept represented by a sum of powers of a base number system, compiles the grammatical description into a first weighted finite state transducer, provides a language specific grammatical description for verbally expressing the numeric concept, compiles the language specific grammatical description into a second weighted finite state transducer, composes the first and second finite state transducers to form a third weighted finite state transducer from which the verbal equivalent of the string can be synthesized, and synthesizes the verbal equivalent from the third weighted finite state transducer.

Abstract: A speech recognition system may be trained with data that is independent from previous acoustics. This method of training is quicker and more cost effective than previous training methods. In training the system, after a vocabulary word is input into the system, a first set of phonemes representative of the vocabulary word is determined. Next, the first set of phonemes is compared with a second set of phonemes representative of a second vocabulary word. The first vocabulary word and the second vocabulary word are different. The comparison generates a confusability index. The confusability index for the second word is a measure of the likelihood that the second word will be mistaken as another vocabulary word, e.g., the first word, already in the system. This process may be repeated for each newly desired vocabulary word.