SIGNLL (pronounce as signal) is the Special Interest Group on Natural Language Learning of the Association for Computational Linguistics (ACL).

The aims and purposes of SIGNLL

Aims

SIGNLL aims to promote research in:

• automated acquisition of syntax, morphology and phonology

• automated acquisition of semantic / ontological structure

• automated acquisition of inter-linguistic correspondences

• learning to recognize or produce spoken and written forms

• modelling human language acquisition theory and processes

Purview

SIGNLL will foster the application and development of new techniques for the automatic analysis of language, including but not limited to:

• case-based, example-based and explanation-based learning

• connectionist, statistical and information-theoretic models

• inductive, deductive and analytic techniques

• clustering and classification procedures

Approaches and Paradigms

SIGNLL emphasizes paradigms which can be exploited automatically:

• corpus-based analysis including automated tagging and testing

• learning in interactive environments with minimal supervision

• automatic preprocessing feeding overtly supervised techniques

• unsupervised and naturally / implicitly supervised techniques

Functions and Activities

SIGNLL aims to perform and encourage the following functions and activities:

• promotion and development of the field and avenues for publication

• provision and coordination of a library of language learning software and data

• facilitation of communication between researchers in this field

• provision of information about relevant research and resources

• development of standard corpora and interface formats for NLL

• coordination of the organization of workshops and symposia

• liaison with other SIGs, funding organizations, etc.