Method and apparatus for cross-lingual communication
A system and method for a highly interactive style of speech-to-speech translation is provided. The interactive procedures enable a user to recognize, and if necessary correct, errors in both speech recognition and translation, thus providing robust translation output than would otherwise be possible. The interactive techniques for monitoring and correcting word ambiguity errors during automatic translation, search, or other natural language processing tasks depend upon the correlation of Meaning Cues and their alignment with, or mapping into, the word senses of third party lexical resources, such as those of a machine translation or search lexicon. This correlation and mapping can be carried out through the creation and use of a database of Meaning Cues, i.e., SELECT. Embodiments described above permit the intelligent building and application of this database, which can be viewed as an interlingua, or language-neutral set of meaning symbols, applicable for many purposes. Innovative techniques for interactive correction of server-based speech recognition are also described.
1. A system providing cross-linguistic communication and providing feedback for machine learning, comprising:
a client component capturing inputs, the client component providing a user interface configured to display a translation of an input term into a different language than an input language, a retranslation from the target language back into the source language, and interface elements enabled for selecting one of whether translations should be verified before transmission, and whether a previous translation should be revised; and
a server component providing the translation and the retranslation to the client component based upon the input term, the server component including,
an interaction manager stored within memory of the server component, the interaction manger configured to request the translation of the inputs and access a database containing data representing a sense of the input term, the sense including a synonym for each different sense of the input term, wherein each different sense includes a different meaning for the term.
2. The system of claim 1 wherein data are derived through one of rule-based techniques, statistically based techniques including neural network techniques, or some combination of rule based and statistically based techniques.
3. The system of claim 2 , wherein the data include synonym sets derived from the translation phrase tables or neural networks of a given statistical machine translation system.
4. The system of claim 3 , wherein the synonym sets are derived from the translation phrase tables or neural networks of a secondary machine translation system which serves as a proxy for the primary translation system.
5. The system of claim 1 further comprising:
the memory storing user profiles defining word sense preferences for each user profile.
6. The system of claim 1 , wherein the server component includes a speech recognition module in communication with the interaction manager, the speech recognition module permitting use of voice commands captured through the client component.
7. The system of claim 1 , wherein the server component includes a text-to-speech module providing an audio signal to the client component for pronunciation of the input term in the different language and the input language.