Optimising a Language Recognition System Through Phoneme-Based Vector Representation

This article analyzes vector representation of phonemes as an alternative to improve a language identification system (LID). CBOW (Continuous Bag-of-Words) and Skip-gram architectures proposed by Mikolov are studied. These models allow predicting words within a context by generating n-dimensional vectors. In this work we will analyze the application of these models in smaller phonetic units or n-grams