Stochastic phonological grammars and acceptability

Computer Science – Computation and Language

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

compressed postscript, 8 pages, 1 figure

Scientific paper

In foundational works of generative phonology it is claimed that subjects can reliably discriminate between possible but non-occurring words and words that could not be English. In this paper we examine the use of a probabilistic phonological parser for words to model experimentally-obtained judgements of the acceptability of a set of nonsense words. We compared various methods of scoring the goodness of the parse as a predictor of acceptability. We found that the probability of the worst part is not the best score of acceptability, indicating that classical generative phonology and Optimality Theory miss an important fact, as these approaches do not recognise a mechanism by which the frequency of well-formed parts may ameliorate the unacceptability of low-frequency parts. We argue that probabilistic generative grammars are demonstrably a more psychologically realistic model of phonological competence than standard generative phonology or Optimality Theory.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Stochastic phonological grammars and acceptability does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Stochastic phonological grammars and acceptability, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Stochastic phonological grammars and acceptability will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-286956

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.