Patent ReferencesMethod and system for natural language translation Recognition unit model training based on competing word and word string models Language independent speech recognition Pronunciation generation in speech recognition Process for the multilingual use of a hidden markov sound model in a speech recognition system Method and apparatus of hierarchically organizing an acoustic model for speech recognition and adaptation of the model to unseen domains Phonetic distance calculation method for similarity comparison between phonetic transcriptions of foreign words Method and apparatus for training a multilingual speech model set Patent #: 6912499 InventorsAssigneeApplicationNo. 09790296 filed on 02/22/2001US Classes:704/243, Creating patterns for matching704/254, Subportions704/255, Specialized models704/277, Translation704/244, Update patterns704/9, Natural language704/256.2, Training of HMM (EPO)704/256, Markov704/238, Distance704/220Analysis by synthesisExaminersPrimary: Edouard, Patrick N.Assistant: Wozniak, James S. Attorney, Agent or FirmInternational ClassesG10L 15/06G10L 15/00 AbstractBootstrapping of a system from one language to another often works well when the two languages share the similar acoustic space. However, when the new language has sounds that do not occur in the language from which the bootstrapping is to be done, bootstrapping does not produce good initial models and the new language data is not properly aligned to these models. The present invention provides techniques to generate context dependent labeling of the new language data using the recognition system of another language. Then, this labeled data is used to generate models for the new language phones.Other References
Field of SearchLINGUISTICSTranslation machine Multilingual or national language support Natural language Hidden Markov (HM) network (EPO) State emission probability (EPO) Continuous density, e.g, Gaussian distribution, Lapalce (EPO) Training of HMM (EPO) Markov Natural language Discrete density, e.g., Vector Quantization preprocessor, look up tables (EPO) With insufficient amount of training data, e.g., state sharing, tying, deleted interpolation (EPO) Duration modeling in HMM, e.g., semi HMM, segmental models, transition probabilities (EPO) Hidden Markov Model (HMM) (EPO) Clustering Creating patterns for matching Update patterns Subportions Specialized models Translation | |