A unified lexical processing framework based on the Margin Infused Relaxed Algorithm. A case study on the Romanian Language

General natural language processing and text-to-speech applications require certain (lexical level) processing steps in order to solve some frequent tasks such as lemmatization, syllabification, lexical stress prediction and phonetic transcription. These steps usually require knowledge of the word’s lexical composition (derivative morphology, inflectional affixes, etc.). For known words all applications use lexicons, but there are always out-of-vocabulary (OOV) words that impede the performance of NLP and speech synthesis applications. In such cases, either rule based or data-driven techniques are used to automatically process these OOV words and generate the desired results. In this paper we describe how the above mentioned tasks can be achieved using a Perceptron with the Margin Infused Relaxed Algorithm (MIRA) and sequence labeling.