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<Paper uid="C96-1063">
  <Title>LEXICAL ACCOMMODATION IN MACHINE-MEDIATED INTERACTIONS</Title>
  <Section position="6" start_page="373" end_page="374" type="concl">
    <SectionTitle>
5 Conclusions and Future Directions
</SectionTitle>
    <Paragraph position="0"> What does this tell us about the design of human-computer interfaces? Recall that these conversations were unconstrained; neither agents, clients nor interpreters, whether human or &amp;quot;machine,&amp;quot; were under instructions to limit or modify their speech in any way. Thus, what we see in these results is the natural tendency of humans to accommodate to their interlocutors in a variety of communication environments. This tendency resulted in the highest level of accommodation in the human-interpreted setting. That level was achieved as a result of mutual accommodation between the two humans involved, both of whom felt a concern for both social standing and communicational efficiency. The level of accommodation observed in the machine-interpreted setting was both lower and less extensive, i.e., it did not persist throughout the conversation.</Paragraph>
    <Paragraph position="1"> We can take advantage of even the moderately high level of accommodation found in the machinemediated setting by building into a language processing system a preference for the lexical items used by the machine. Coupled with accommodations in other aspects of language such as discourse and syntactic complexity, fluency, and speaking rate (Fais et al., in press), lexical accommodation can inform a language model to improve language processing performance by exploiting the relationships between human speech and the speech of the machine interface.</Paragraph>
    <Paragraph position="2"> Specifically, candidates for speech recognition or parsing could receive higher preference scores if they include lexical items or structures previously encountered in the discourse. Alternatively,  preferences based on accommodation could be built directly into a language model for speech recognition or decision tree for parsing.</Paragraph>
    <Paragraph position="3"> We would like to investigate the possibility of increasing the level of accommodation in the machine~ mediated setting. Ideally, we would like users' accommodation to a machine interface to be as high as possible so that the lexical variability of users' speech can be as constrained as possible. One way is to use the resources of a multimedia environment to replicate the effect of the human-interpreted setting by providing the machine interface with a human-like persona. A number of human-computer systems already include such a feature (e.g., Ball and Ling, 1995; Bertenstam et al., 1995; Webber, 1995); it remains to be seen if it will have the desired effect on lexical accommodation. On the other hand, there is evidence that encouraging users to interact with machines as if they were humans may actually undermine the quality of the users' speech from the point of view of language processing. Work in the area of disfluencies in human-to-machine speech suggests that humans do, in fact, &amp;quot;clean up&amp;quot; their speech for machines (Suhm et al., 1994). These advantages may be lost if humans are encouraged to treat a machine interface as if it were human.</Paragraph>
    <Paragraph position="4"> Empirical investigation is required to determine if an optimal balance can be reached.</Paragraph>
    <Paragraph position="5"> We have suggested that the design of speech recognition and language processing systems can take advantage of users' lexical accommodation to machine interfaces to improve system performance. This, in turn, would allow the construction of systems which make fewer demands on the willingness of users to adjust to misrecognitions and nfisunderstandings, and which encourage users to interact with computer interpreters as if they were interacting with human interpreters. This result would also have the effect of further increasing lexical accommodation from users.</Paragraph>
  </Section>
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