Abstract: Speech is processed that may be colored by speech accent. A method for recognizing speech includes maintaining a model of speech accent that is established based on training speech data, wherein the training speech data includes at least a first set of training speech data, and wherein establishing the model of speech accent includes not using any phone or phone-class transcription of the first set of training speech data. Related systems are also presented. A system for recognizing speech includes an accent identification module that is configured to identify accent of the speech to be recognized; and a recognizer that is configured to use models to recognize the speech to be recognized, wherein the models include at least an acoustic model that has been adapted for the identified accent using training speech data of a language, other than primary language of the speech to be recognized, that is associated with the identified accent. Related methods are also presented.

Abstract: A system and associated methods determine the semantic similarity of different sentences to one another. A particularly appropriate application of the present invention is to automatic processing of Chinese-language text, for example, for document retrieval. A method for computing the similarity between a first and a second set of words comprises identifying a word of the second set of words as being most similar to a word of the first set of words, wherein the word of the second set of words need not be identical to the word of the first set of words; and computing a score of the similarity between the first and second set of words based at least in part on the word of the second set of words.

Abstract: A system and associated methods identify documents relevant to an inputted natural-language user query. One associate method includes: selecting a set of keywords from the user query; determining at least one word, not necessarily found in the user query, that is semantically similar to a keyword of the set of keywords; using the set of keywords and the at least one word to determining a subset of word sets from a database of pre-stored word sets, wherein the pre-stored word sets are each pre-associated with at least one document; determining a plurality of word sets, from the subset of word sets, that is most semantically similar to the user query; and identifying documents that have been pre-associated with the plurality of word sets as being relevant to the natural-language user query.