<?xml version="1.0" standalone="yes"?>
<Paper uid="H05-1104">
  <Title>Proceedings of Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing (HLT/EMNLP), pages 827-834, Vancouver, October 2005. c(c)2005 Association for Computational Linguistics Parallelism in Coordination as an Instance of Syntactic Priming: Evidence from Corpus-based Modeling</Title>
  <Section position="3" start_page="827" end_page="828" type="intro">
    <SectionTitle>
2 Adaptation
</SectionTitle>
    <Paragraph position="0"> Psycholinguistic studies have shown that priming affects both speech production (Bock, 1986) and comprehension (Branigan et al., 2005). The importance of comprehension priming has also been noted by the speech recognition community (Kuhn and de Mori, 1990), who use so-called caching language models to improve the performance of speech comprehension software. The concept of caching language models is quite simple: a cache of recently seen words is maintained, and the probability of words in the cache is higher than those outside the cache.</Paragraph>
    <Paragraph position="1"> While the performance of caching language models is judged by their success in improving speech recognition accuracy, it is also possible to use an abstract measure to diagnose their efficacy more closely. Church (2000) introduces such a diagnostic for lexical priming: adaptation probabilities. Adaptation probabilities provide a method to separate the general problem of priming from a particular implementation (i.e., caching models). They measure the amount of priming that occurs for a given construction, and therefore provide an upper limit for the performance of models such as caching models.</Paragraph>
    <Paragraph position="2"> Adaptation is based upon three concepts. First is the prior, which serves as a baseline. The prior measures the probability of a word appearing, ignoring the presence or absence of a prime. Second is the positive adaptation, which is the probability of a word appearing given that it has been primed. Third is the negative adaptation, the probability of a word appearing given it has not been primed.</Paragraph>
    <Paragraph position="3"> In Church's case, the prior and adaptation probabilities are estimated as follows. If a corpus is divided into individual documents, then each document is then split in half. We refer to the halves as the prime set (or prime half) and the target set (or target half).1 We measure how frequently a document half contains a particular word. For each word w, there are four combinations of the prime and target halves containing the word. This gives us four frequencies to measure, which are summarized in the following table: fwp,t fw -p,t fwp,-t fw -p,-t These frequencies represent: fwp,t = # of times w occurs in prime set and target set fw -p,t = # of times w occurs in target set but not prime set fwp,-t = # of times w occurs in prime set but not target set fw -p,-t = # of times w does not occur in either target set or prime set In addition, let N represent the sum of these four frequencies. From the frequencies, we may formally define the prior, positive adaptation and negative adaptation:</Paragraph>
    <Paragraph position="5"> In the case of lexical priming, Church observes that P+ Pprior &gt; P[?]. In fact, even in cases when Pprior quite small, P+ may be higher than 0:8. Intuitively, a positive adaptation which is higher than the prior entails that a word is likely to reappear in the target set given that it has already appeared in the prime set. We intend to show that adaptation probabilities provide evidence that syntactic constructions behave 1Our terminology differs from that of Church, who uses 'history' to describe the first half, and 'test' to describe the second. Our terms avoid the ambiguity of the phrase 'test set' and coincide with the common usage in the psycholinguistic literature.  similarity to lexical priming, showing positive adaptation P+ greater than the prior. As P[?] must become smaller than Pprior whenever P+ is larger than Pprior, we only report the positive adaptation P+ and the prior Pprior.</Paragraph>
    <Paragraph position="6"> While Church's technique was developed with speech recognition in mind, we will show that it is useful for investigating psycholinguistic phenomenon. However, the connection between cognitive phenomenon and engineering approaches go in both directions: it is possible that syntactic parsers could be improved using a model of syntactic priming, just as speech recognition has been improved using models of lexical priming.</Paragraph>
  </Section>
class="xml-element"></Paper>