Natural Language Processing and Computational Linguistics 1

Language is one of the central tools in our social and professional life. Among other things, it acts as a medium for transmitting ideas, information, opinions and feelings, as well as for persuading, asking for information, giving orders, etc. Computer Science began to gain an interest in language as soon as the field itself emerged, notably within the field of Artificial Intelligence (AI). The Turing test, one of the first tests developed to judge whether a machine is intelligent or not, stipulates that to be considered intelligent, a machine must possess conversational abilities that are comparable to those of a human being [TUR 50]. This implies that an intelligent machine must possess comprehension and production abilities, in the broadest sense of these terms. Historically, natural language processing (NLP) got itself focused on the potential for applying such technology to the real world in a very short span of time, particularly with machine translation (MT) during the Cold War. This began with the first machine translation system which was developed as the brainchild of a joint project between the University of Georgetown and IBM in the United States [DOS 55, HUT 04]. This work was not crowned with the success that was expected, as the researchers soon realized that a deep understanding of the linguistic system is a prerequisite for any comprehensive application of this kind. This discovery, presented in the famous report by automatic language processing advisory committee (ALPAC), had a considerable impact upon machine translation work and on the field of NLP in general. Today, even though NLP is largely industrialized, the interest in basic language processing has not waned. In fact, whatever the application of modern NLP, the use of a basic language processing unit such as a morphological, syntactic, recognition or speech synthesis analyzer is almost always indispensable (see [JON 11] for a more complete review of the history of NLP).