The workshop focuses on linguistic complexity and its relevance in the field of natural language processing. We propose a cross-discipline workshop that foster exchange of ideas between people in the area of artificial intelligence and natural language processing and people dealing with natural language complexity from a cognitive or a theoretical point of view. The main objective of this workshop is to bring together researchers from different areas that have in common their interest on linguistic complexity (from a practical or theoretical perspective) boosting the interchange of knowledge and methods between specialists that have approached complexity from different viewpoints. We want to promote interdisciplinarity among researchers that are dealing with any type of language complexity.
Complexity has become an important concept in several scientific disciplines. There has been a lot of research on complexity and complex systems in the natural sciences, economics, social sciences and, now, also increasingly in linguistics. Moreover, linguistic complexity may be a key point in automatic natural language processing, since results in that field may condition the design of language technologies.
Are all languages equally complex? Does it make sense to compare the complexity of languages? Can languages differ in complexity? Complexity is a controversial concept in linguistics. Until recently, natural language complexity has not been widely researched and still not clear how complexity has to be defined and measured. Twentieth century most theoretical linguists have defended the equi-complexity dogma, which states that the total complexity of a natural language is fixed because sub-complexities in linguistic sub-systems trade off. This idea of equi-complexity, seen for decades as an unquestioned truism of linguistics, has begun to be explicitly questioned in recent years. There have been attempts to apply the concept of complexity used in other disciplines in order to find useful tools to calculate linguistic complexity. Information theory, computational models or the theory of complex systems are examples of areas that provide measures to quantitatively evaluate linguistic complexity.
Many models have been proposed to confirm or refute the hypothesis of linguistic equi-complexity. The tools, criteria and measures to quantify the level of complexity of languages vary and depend on the specific research interests and on the definition of complexity adopted. In fact, there is no agreement in the literature about how to define complexity. Instead, in the literature, we can find a variety of approaches that has led to linguistic complexity taxonomy: absolute complexity vs. relative complexity; global complexity vs. local complexity; system complexity vs. structural complexity, etc. Currently, there is no clear solution to quantify the complexity of languages and each of the proposed models has advantages and disadvantages.
In this workshop, we are interested in contributions introducing new methods, models, definitions and measures to assess natural languages complexity (in human and automatic processing). We are especially interested in computational and formal approaches to linguistic complexity.
Proceedings are now available here!