Abstract: A phrase-based translation system and method includes a statistically integrated phrase lattice (SIPL) (H) which represents an entire translational model. An input (I) is translated by determining a best path through an entire lattice (S) by performing an efficient composition operation between the input and the SIPL. The efficient composition operation is performed by a multiple level search where each operand in the efficient composition operation represents a different search level.

Abstract: A natural language business system and method is developed to understand the underlying meaning of a person's speech, such as during a transaction with the business system. The system includes a speech recognition engine, and action classification engine, and a control module.

Abstract: A system and method for speech recognition includes generating a set of likely hypotheses in recognizing speech, rescoring the likely hypotheses by using semantic content by employing semantic structured language models, and scoring parse trees to identify a best sentence according to the sentence's parse tree by employing the semantic structured language models to clarify the recognized speech.

Abstract: The present invention relates to a novel drug delivery and release system, i.e. Self-emulsifying Drug Delivery System (SEDDS), of butylphthalide, to a preparation process thereof, and to a use thereof in a pharmaceutical formulation. The drug delivery system comprises as essential ingredients 1% to 65% of butylphthalide and 10% to 65% of a emulsifying agent, together with various excipients as required depending on the desired dosage forms. The present invention significantly increases the contact area between butylphthalide and the mucous membrane of the gastrointestinal tract, and therefore improves the absorptivity of the drug.

Abstract: Techniques for employing improved prompts in a speech-to-speech translation system are disclosed. By way of example, a technique for use in indicating a dialogue turn in an automated speech-to-speech translation system comprises the following steps/operations. One or more text-based scripts are obtained. The one or more text-based scripts are synthesizable into one or more voice prompts. At least one of the one or more voice prompts is synthesized for playback from at least one of the one or more text-based scripts, the at least one synthesized voice prompt comprising an audible message in a language understandable to a speaker interacting with the speech-to-speech translation system, the audible message indicating a dialogue turn in the automated speech-to-speech translation system.

Abstract: Techniques for assisting in translation are provided. A speech recognition hypothesis is obtained, corresponding to a source language utterance. Information retrieval is performed on a supplemental database, based on a situational context, to obtain at least one word string that is related to the source language utterance. The speech recognition hypothesis and the word string are then formatted for display to a user, to facilitate an appropriate selection by the user for translation.

Abstract: Techniques for enhanced linguistic transformation are disclosed. For example, a method of linguistic transformation includes the steps of providing at least one input to a plurality of modules, wherein at least one module has a different configuration than at least another module, obtaining at least one output from each of at least a subset of the plurality of modules, and generating a set of distinct outputs. The input and the output include linguistic representations and at least a portion of the output is a result of applying one or more linguistic transformations to at least a portion of the input. Techniques for displaying a plurality of results so as to emphasize component-level differences are also disclosed.

Abstract: Techniques for adapting a virtual keyboard for multilingual input are disclosed. By way of example, a method of adapting a virtual keyboard for multilingual input includes the steps of detecting an input language and displaying a virtual keyboard corresponding to the input language upon detection of the input language. The identifying step may include automatic identification of an input language, such as by one or more language recognition modules, or it may include manual selection of an input language and activation of at least one language recognition module operative to recognize at least the input language upon selection of the input language.

Abstract: A technique for context adaptation of a speech-to-speech translation system is provided. A plurality of sets of paralinguistic attribute values is obtained from a plurality of input signals. Each set of the plurality of sets of paralinguistic attribute values is extracted from a corresponding input signal of the plurality of input signals via a corresponding classifier of a plurality of classifiers. A final set of paralinguistic attribute values is generated for the plurality of input signals from the plurality of sets of paralinguistic attribute values. Performance of at least one of a speech recognition module, a translation module and a text-to-speech module of the speech-to-speech translation system is modified in accordance with the final set of paralinguistic attribute values for the plurality of input signals.

Abstract: A computer-implemented method for creating a disfluency translation lattice includes providing a plurality of weighted finite state transducers including a translation model, a language model, and a phrase segmentation model as input, performing a cascaded composition of the weighted finite state transducers to create a disfluency translation lattice, and storing the disfluency translation lattice to a computer-readable media.

Abstract: An apparatus and method that integrates both phrase-based and free-form speech-to-speech translation approaches using probability models. The starting step of the method is to receive vocal communication in a source language. Then store the received vocal communication. Then decipher the content of the vocal communication. Then locate in a multilingual dictionary module the corresponding translation of the deciphered vocal communication provided a preset sentence exists in a speech recognition module for the vocal communication. Then translate the vocal communication into the target language provided there is no corresponding translation located in the multilingual dictionary module. Then synthesize the translated target language when there is no corresponding translation for the vocal communication in the multilingual dictionary module. Then store the sound of the translated target language. Then play the sound of the translated target language.

Abstract: A phrase-based translation system and method includes a statistically integrated phrase lattice (SIPL) (H) which represents an entire translational model. An input (I) is translated by determining a best path through an entire lattice (S) by performing an efficient composition operation between the input and the SIPL. The efficient composition operation is performed by a multiple level search where each operand in the efficient composition operation represents a different search level.

Abstract: Techniques for assisting in translation are provided. A speech recognition hypothesis is obtained, corresponding to a source language utterance. Information retrieval is performed on a supplemental database, based on a situational context, to obtain at least one word string that is related to the source language utterance. The speech recognition hypothesis and the word string are then formatted for display to a user, to facilitate an appropriate selection by the user for translation.

Abstract: Techniques for detecting data anomalies in a natural language understanding (NLU) system are provided. A number of categorized sentences, categorized into a number of categories, are obtained. Sentences within a given one of the categories are clustered into a number of sub clusters, and the sub clusters are analyzed to identify data anomalies. The clustering can be based on surface forms of the sentences. The anomalies can be, for example, ambiguities or inconsistencies. The clustering can be performed, for example, with a K-means clustering algorithm.

Abstract: Techniques for employing improved prompts in a speech-to-speech translation system are disclosed. By way of example, a technique for use in indicating a dialogue turn in an automated speech-to-speech translation system comprises the following steps/operations. One or more text-based scripts are obtained. The one or more text-based scripts are synthesizable into one or more voice prompts. At least one of the one or more voice prompts is synthesized for playback from at least one of the one or more text-based scripts, the at least one synthesized voice prompt comprising an audible message in a language understandable to a speaker interacting with the speech-to-speech translation system, the audible message indicating a dialogue turn in the automated speech-to-speech translation system.

Abstract: A natural language business system and method is developed to understand the underlying meaning of a person's speech, such as during a transaction with the business system. The system includes a speech recognition engine, and action classification engine, and a control module. The control module causes the system to execute an inventive method wherein the speech recognition and action classification models may be recursively optimized on an unisolated performance metric that is pertinent to the overall performance of the natural language business system, as opposed to the isolated model-specific criteria previously employed.

Abstract: A method, apparatus and computer instructions is provided for fast semi-automatic semantic annotation. Given a limited annotated corpus, the present invention assigns a tag and a label to each word of the next limited annotated corpus using a parser engine, a similarity engine, and a SVM engine. A rover then combines the parse trees from the three engines and annotates the next chunk of limited annotated corpus with confidence, such that the efforts required for human annotation is reduced.

Abstract: Techniques for providing an automated conversational name dialing system for placing a call in response to an input by a user. One technique begins with the step of analyzing an input from a user, wherein the input includes information directed to identifying an intended recipient of a telephone call from the user. At least one candidate for the intended recipient is identified in response to the input, wherein the at least one candidate represents at least one potential match between the intended recipient and a predetermined vocabulary. A confidence measure indicative of a likelihood that the at least one candidate is the intended recipient is determined, and additional information is obtained from the user to increase the likelihood that the at least one candidate is the intended recipient, based on the determined confidence measure.

Abstract: A system and method for speech recognition includes generating a set of likely hypotheses in recognizing speech, rescoring the likely hypotheses by using semantic content by employing semantic structured language models, and scoring parse trees to identify a best sentence according to the sentence's parse tree by employing the semantic structured language models to clarify the recognized speech.

Abstract: A method and apparatus are disclosed for training a pattern recognition system, such as a speech recognition system, using an improved objective function. The concept of rank likelihood, previously applied only to the decding process, is applied in a novel manner to the parameter estimation of the training phase of a pattern recognition system. The disclosed objective function is based on a pseudo-rank likelihood that not only maximizes the likelihood of an observation for the correct class, but also minimizes the likelihoods of the observation for all other classes, such that the discrimination between classes is maximized. A training process is disclosed that utilizes the pseudo-rank likelihood objective function to identify model parameters that will result in a pattern recognizer with the lowest possible recognition error rate. The discrete nature of the rank-based rank likelihood objective function is transformed to allow the parameter estimations to be optimized during the training phase.