In the last decade machine learning techniques based on logic such as Inductive Logic Programming (ILP) have started being used in learning grammars from corpora. While the first approaches were based on the translation of grammar into first-order predicate logic, an attempt has been made recently to adapt the ILP learning schema to the feature constraint logic of typed-unification grammars. In...

To avoid some conceptual and methodological pitfalls found in traditional artificial grammar learning tasks, we developed a new method of measuring implicit learning using immediate memory span. Subjects were presented with sequences generated by an artificial grammar and were asked to reproduce the patterns by pressing buttons on a response box. After exposure to these sequences, subjects show...

Despite the fact that in many countries a great deal of classroom time and self-study is devoted to the learning of grammar, it appears that very little theoretical consideration is given in teacher education programmes either to the nature of the grammatical code which is to be acquired by learners nor to theories of how grammar is learnt in school-based contexts. As stated earlier in this vol...

We are interested in educational software tools that can generate novel jazz solos in a style representative of a body of performed work, such as solos by a specific artist. Our approach is to provide automated learning of a grammar from a corpus of performances. Use of a grammar is robust, in that it can provide generation of solos over novel chord changes, as well as ones used in the learning...

The study illuminates the effectiveness of Computer Assisted Learning in Tamil Grammar for the learners at standard VIII. Computer Assisted Learning is particularly beneficial for any student learning a language. It promotes peer interaction, which helps the development of language and the learning of concepts with content. It is important to assign TLL (Tamil Language Learners) to different te...

The paper follows a discourse on computer-assisted language learning. We examine problems of foreign language teaching and learning and introduce a metamodel that can be used to define learning models of language grammar structures in order to support teacher/student interaction. Special attention is paid to the concept of a virtual language lab. Our approach to language education assumes to en...

Considerable evidence suggests that people acquire artificial grammars incidentally and implicitly, an indispensable capacity for the acquisition of music or language. However, less research has been devoted to exploring constraints affecting incidental learning. Within the domain of music, the extent to which Narmour's (1990) melodic principles affect implicit learning of melodic structure was...

This paper describes an algorithm for spoken language acquisition through a human-robot interface based on speech, vision, and behavior. In this algorithm the grounded language knowledge is represented by graphical statistical models consisting of hidden Markov models and stochastic context-free grammar. The learning of the lexicon is based on the independence between speech and visual features...

The explanation of heterogeneous multivariate time series data is a central problem in many applications. The problem requires two major data mining challenges to be addressed simultaneously: Learning models that are humaninterpretable and mining of heterogeneous multivariate time series data. The intersection of these two areas is not adequately explored in the existing literature. To address ...

This paper describes Grammar Learning by Partition Search, a general method for automatically constructing grammars for a range of parsing tasks. Given a base grammar, a training corpus, and a parsing task, Partition Search constructs an optimised probabilistic context-free grammar by searching a space of nonterminal set partitions, looking for a partition that maximises parsing performance and...