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: A system and method for speech-to-speech translation using a translation system includes designating separate input channels for each of a plurality of speakers. In response to speech from a first channel in a first language, the speech from the first channel is translated to a second language, and in response to speech from the second channel in a second language, the speech from the second channel is translated to the first language. Translating the speech from the first channel and translating the speech from the second channel are performed concurrently.

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: 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: Systems and methods for active learning of statistical machine translation systems through dynamic creation and updating of parallel corpus. The systems and methods provided create accurate parallel corpus entries from a test set of sentences, words, phrases, etc. by calculating confidence scores for particular translations. Translations with high confidence scores are added directly to the corpus and the translations with low confidence scores are presented to human translations for corrections.

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: A concept-based back translation system includes a target language semantic parser module, a source language semantic parser module, a bi-directional machine translation module, a relevancy judging module, and a back translation display module.

Abstract: A concept-based back translation system includes a target language semantic parser module, a source language semantic parser module, a bi-directional machine translation module, a relevancy judging module, and a back translation display module.

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 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 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: A system and method for speech-to-speech translation using a translation system includes designating separate input channels for each of a plurality of speakers. In response to speech from a first channel in a first language, the speech from the first channel is translated to a second language, and in response to speech from the second channel in a second language, the speech from the second channel is translated to the first language. Translating the speech from the first channel and translating the speech from the second channel are performed concurrently.

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: A system and method for training a statistical machine translation model and decoding or translating using the same is disclosed. A source word versus target word co-occurrence matrix is created to define word pairs. Dimensionality of the matrix may be reduced. Word pairs are mapped as vectors into continuous space where the word pairs are vectors of continuous real numbers and not discrete entities in the continuous space. A machine translation parametric model is trained using an acoustic model training method based on word pair vectors in the continuous space.

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: 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: A system and method for automatic user training in speech-to-speech translation includes integrating an automatic user response system configured to be responsive to a plurality of training items and selecting a training item from the plurality of training items. For the selected training item, in response to an utterance in a first language, the utterance is translated into a second language, and a response to the utterance in the second language is generated. A simulated action corresponding with the response in accordance with a user speaking the second language is also generated. The response and simulated action are output as a learning exercise for learning operations of the automatic user response system.

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.