Abstract: A real-time open domain speech translation system for simultaneous translation of a spoken presentation that is a spoken monologue comprising one of a lecture, a speech, a presentation, a colloquium, and a seminar. The system includes an automatic speech recognition unit configured for accepting sound comprising the spoken presentation in a first language and for continuously creating word hypotheses, and a machine translation unit that receives the hypotheses, wherein the machine translation unit outputs a translation, into a second language, from the spoken presentation.

Abstract: A method and apparatus are provided for updating the vocabulary of a speech translation system for translating a first language into a second language including written and spoken words. The method includes adding a new word in the first language to a first recognition lexicon of the first language and associating a description with the new word, wherein the description contains pronunciation and word class information. The new word and description are then updated in a first machine translation module associated with the first language. The first machine translation module contains a first tagging module, a first translation model and a first language module, and is configured to translate the new word to a corresponding translated word in the second language. Optionally, the invention may be used for bidirectional or multi-directional translation.

Abstract: A real-time open domain speech translation system for simultaneous translation of a spoken presentation that is a spoken monologue comprising one of a lecture, a speech, a presentation, a colloquium, and a seminar. The system includes an automatic speech recognition unit configured for accepting sound comprising the spoken presentation in a first language and for continuously creating word hypotheses, and a machine translation unit that receives the hypotheses, wherein the machine translation unit outputs a translation, into a second language, from the spoken presentation.

Abstract: A real-time open domain speech translation system for simultaneous translation of a spoken presentation that is a spoken monologue comprising one of a lecture, a speech, a presentation, a colloquium, and a seminar. The system includes an automatic speech recognition unit configured for accepting sound comprising the spoken presentation in a first language and for continuously creating word hypotheses, and a machine translation unit that receives the hypotheses, wherein the machine translation unit outputs a translation, into a second language, from the spoken presentation.

Abstract: A speech translation system and methods for cross-lingual communication that enable users to improve and modify content and usage of the system and easily abort or reset translation. The system includes a speech recognition module configured for accepting an utterance, a machine translation module, an interface configured to communicate the utterance and proposed translation, a correction module and an abort action unit that removes any hypotheses or partial hypotheses and terminates translation. The system also includes modules for storing favorites, changing language mode, automatically identifying language, providing language drills, viewing third party information relevant to conversation, among other things.

Abstract: A field maintainable class-based translation system and apparatus with components that ease use by linguistically untrained users is disclosed. The apparatus includes modules for recovering errors, extending and customizing language coverage and increasing the speed of effective communication.

Abstract: A method and apparatus are provided for updating the vocabulary of a speech translation system for translating a first language into a second language including written and spoken words. The method includes adding a new word in the first language to a first recognition lexicon of the first language and associating a description with the new word, wherein the description contains pronunciation and word class information. The new word and description are then updated in a first machine translation module associated with the first language. The first machine translation module contains a first tagging module, a first translation model and a first language module, and is configured to translate the new word to a corresponding translated word in the second language.

Abstract: A real-time open domain speech translation system for simultaneous translation of a spoken presentation that is a spoken monologue comprising one of a lecture, a speech, a presentation, a colloquium, and a seminar. The system includes an automatic speech recognition unit configured for accepting sound comprising the spoken presentation in a first language and for continuously creating word hypotheses, and a machine translation unit that receives the hypotheses, wherein the machine translation unit outputs a translation, into a second language, from the spoken presentation.

Abstract: A method for myoelectric-based processing of speech. The method includes capturing a myoelectric signal from a user using at least one electrode, wherein the electrode converts an ionic current generated by muscle contraction into an electric current. The method also includes amplifying the electric current, filtering the amplified electric current, and converting the filtered electric current into a digital signal. The method further includes transmitting the myoelectric signal to a digital device, transforming the digital signal into a written representation using an automatic speech recognition method, and generating an audible output from the written representation using a speech synthesis method.

Abstract: The method of the present invention is comprised of the steps of locating an error within a recognition hypothesis. A repair hypothesis is generated for the located error from a secondary input signal. At least a portion of the recognition hypothesis is correlated with the repair hypothesis to produce a new hypothesis for the located error. The located error is replaced with the new hypothesis. It has been determined that when the primary and secondary input signals are cross-modal, the chances that the error will be repeated are so low that the correlation step becomes optional.