Unsupervised Prediction of Acceptability Judgements

Grammaticality, Acceptability, and Probability: A Probabilistic View of Linguistic Knowledge

The question of whether humans represent grammatical knowledge as a binary condition on membership in a set of well-formed sentences, or as a probabilistic property has been the subject of debate among linguists, psychologists, and cognitive scientists for many decades. Acceptability judgments present a serious problem for both classical binary and probabilistic theories of grammaticality. Thes...

Acceptability Prediction by Means of Grammaticality Quantification

We propose in this paper a method for quantifying sentence grammaticality. The approach based on Property Grammars, a constraint-based syntactic formalism, makes it possible to evaluate a grammaticality index for any kind of sentence, including ill-formed ones. We compare on a sample of sentences the grammaticality indices obtained from PG formalism and the acceptability judgements measured by ...

Must diphone synthesis be so unnatural?

An English utterance was synthesized in four versions using sets of diphones produced under four different prosodic and contextual conditions. The synthesis used either accented diphones only or appropriately located accented and unaccented diphones, with each of these conditions being repeated using neutral-context and differentiated-context diphones. They were presented to two listener groups...

Cross-linguistic network structure effects on nonword acceptability judgements

Alert correlation and prediction using data mining and HMM

Intrusion Detection Systems (IDSs) are security tools widely used in computer networks. While they seem to be promising technologies, they pose some serious drawbacks: When utilized in large and high traffic networks, IDSs generate high volumes of low-level alerts which are hardly manageable. Accordingly, there emerged a recent track of security research, focused on alert correlation, which ext...