Data processing: speech signal processing – linguistics – language – Linguistics – Translation machine
Reexamination Certificate
1998-11-23
2001-02-27
Isen, Forester W. (Department: 2747)
Data processing: speech signal processing, linguistics, language
Linguistics
Translation machine
C704S002000
Reexamination Certificate
active
06195631
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of Invention
The invention relates to automatic language translation. In particular, the invention relates to a method and apparatus for training language translation systems automatically from bilingual data.
2. Description of Related Art
Language translation systems have existed for several years. These systems typically require a large hand-coding effort to construct translation lexicons and rule sets. This type of manual coding is expensive in terms of time and the level of expertise required. A number of approaches have been proposed for automatically learning translation models from examples provided by human translators. However, the types of models created suffer from a number of problems, such as low translation quality or a requirement for very large amounts of training data.
SUMMARY OF THE INVENTION
A method and apparatus for automatically constructing hierarchical transduction models for language translation is presented. The input to the construction process may be a database of examples each consisting of a transcribed speech utterance and its translation into another language. A translation pairing score is assigned (or computed) for translating a word in the source language into each of the possible translations it has in the target language. For each instance of the resulting training dataset, a head transducer may be constructed that translates the source string into the target string by splitting the source string into a source head word, the words preceding the source head word, and the words following the source head word. This process may be performed recursively to generate a set of transducer fragments. The transducer fragments may form a statistical head transducer model. The head transducer translation model may then be input into a transduction search module.
These and other features and advantages of this invention are described or apparent from the following detailed description of the preferred embodiments.
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Alshawi Hiyan
Douglas Shona
AT&T Corporation
Edouard Patrick N.
Isen Forester W.
Oliff & Berridg,e PLC
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