Finite state methods have been in common use in various areas of natural language processing (NLP) for many years. A series of specialized workshops in this area illustrates this. In 1996, András Kornai organized a very successful workshop entitled Extended Finite State Models of Language. One of the results of that workshop was a special issue of Natural Language Engineering (Volume 2, Number 4). In 1998, Kemal Oflazer organized a workshop called Finite State Methods in Natural Language Processing. A selection of submissions for this workshop were later included in a special issue of Computational Linguistics (Volume 26, Number 1). Inspired by these events, Lauri Karttunen, Kimmo Koskenniemi and Gertjan van Noord took the initiative for a workshop on finite state methods in NLP in Helsinki, as part of the European Summer School in Language, Logic and Information. As a related special event, the 20th anniversary of two-level morphology was celebrated. The appreciation of these events led us to believe that once again it should be possible, with some additional submissions, to compose an interesting special issue of this journal.

Natural language (NL) has evolved to facilitate human communication. It enables the speaker to make the listener's mind wander among her experiences and mental associations roughly according to the intentions of the speaker. The speaker and the listener usually share experiences and expectations, and they use mostly the same units and rules of a shared NL. Written language functions similarly, but in a less interactive way, with fewer possibilities for feedback.Both the symbols of NL (i.e. words or morphemes), and their arrangements are meaningful. Not with universal and precise meanings, but similar enough among different speakers and accurate enough for the communication mostly to succeed.NLs are mostly very large systems. Hundreds of thousands of words and infinitely many possible utterances. Even inflection alone might produce huge numbers of forms, e.g. more than ten thousand distinct forms out of every Finnish verb entry.NL processing (for IR or any other purpose) must cope with phenomena like (1) inflection and compounding, (2) synonymy, (3) polysemy, (4) ambiguity, (5) anaphora and (6) head-modifier relations among words and phrases.Language technology can neutralize much of the effect of these 'inconveniences' inherent with NL, but what kinds of advantages could NL have?

A source of potential systematic errors in information retrieval is identified and discussed. These errors occur when base form reduction is applied with a (necessarily) finite dictionary. Formal methods for avoiding this error source are presented, along with some practical complexities met in its implementation.

A language independent model for recognition and production of word forms is presented. This "two-level model" is based on a new way of describing morphological alternations. All rules describing the morphophonological variations are parallel and relatively independent of each other. Individual rules are implemented as finite state automata, as in an earlier model due to Martin Kay and Ron Kaplan. The two-level model has been implemented as an operational computer programs in several places. A number of operational two-level descriptions have been written or are in progress (Finnish, English, Japanese, Rumanian, French, Swedish, Old Church Slavonic, Greek, Lappish, Arabic, Icelandic). The model is bidirectional and it is capable of both analyzing and synthesizing word-forms.