Language identification of individualwords in a multilingual automatic speech recognition system
Andrea Hategan, Bogdan Barliga, Ioan Tăbuş · 2009
This paper presents a new algorithm for identifying the language of words in a multilingual automatic speech recognition system. The new algorithm uses as input written words and it is composed of a method for language modelling and a method to select the language of a given word based on the available models. We also present two selection rules for the model's parameters. One of the rules uses a free parameter that controls the accuracy of the resulted model, as well as its size. On average, the classification accuracy of the new algorithm is above 70% for the first best and above 80% for the first two best.