Patent ID: 8798984
Filing Date: 2014-08-05
Classification: G06F,G10L

Abstract:
1. A method for building a language model for a translation system, comprising: providing a language model which includes a weight for each of a set of n-gram factored features which have been identified in a corpus of sentences in a target language; providing a set of machine translations in the target language of a same source string in a source language; providing a first relative ranking of first and second of the machine translations, based on a computed translation scoring metric; computing counts of n-gram factored features for the first and second machine translations; determining a second relative ranking of the first and second translations using the weights of the language model for the n-gram factored features of the first and second machine translations and the computed counts; comparing the first and second relative rankings to determine whether they are in agreement; and where, based on the comparison, the rankings are not in agreement, updating one or more of the weights in the language model as a function of a measure of confidence in the weight, the measure of confidence being a function of previous observations of the n-gram factored feature in the method.