Abstract not found

Cue phrases are linguistic expressions such as now and well that function as explicit indicators of the structure of a discourse. For example, now may signal the beginning of a subtopic or a return to a previous topic, while well may mark subsequent material as a response to prior material, or as an explanatory comment. However, while cue phrases may convey discourse structure, each also has one or more alternate uses. While incidentally may be used sententially as an adverbial, for example, the discourse use initiates a digression. Although distinguishing discourse and sentential uses of cue phrases is critical to the interpretation and generation of discourse, the question of how speakers and hearers accomplish this disambiguation is rarely addressed. This paper reports results of empirical studies on discourse and sentential uses of cue phrases, in which both text-based and prosodic features were examined for disambiguating power. Based on these studies, it is proposed that discourse versus sentential usage may be distinguished by intonational features, specifically, pitch accent and prosodic phrasing. A prosodic model that characterizes these distinctions is identified. This model is associated with features identifiable from text analysis, including orthography and part of speech, to permit the application of the results of the prosodic analysis to the generation of appropriate intonational features for discourse and sentential uses of cue phrases in synthetic speech. 1.

We present an algorithm for simultaneously constructing both the syntax and semantics of a sentence using a Lexicalized Tree Adjoining Grammar (LTAG). This approach captures naturally and elegantly the interaction between pragmatic and syntactic constraints on descriptions in a sentence, and the inferential interactions between multiple descriptions in a sentence. At the same

What kinds of social relationships can people have with computers? Are there activities that computers can engage in that actively draw people into relationships with them? What are the potential benefits to the people who participate in these human-computer relationships? To address these questions this work introduces a theory of Relational Agents, which are computational artifacts designed to build and maintain long-term, social-emotional relationships with their users. These can be purely software humanoid animated agents--as developed in this work--but they can also be non-humanoid or embodied in various physical forms, from robots, to pets, to jewelry, clothing, hand-helds, and other interactive devices. Central to the notion of relationship is that it is a persistent construct, spanning multiple interactions; thus, Relational Agents are explicitly designed to remember past history and manage future expectations in their interactions with users. Finally, relationships are fundamentally social and emotional, and detailed knowledge of human social psychology--with a particular emphasis on the role of affect--must be incorporated into these agents if they are to effectively leverage the mechanisms of human social cognition in order to build relationships in the most natural manner possible. People build

Abstract not found

Explaining speakers' choice of which items to emphasize or de-emphasize intonationally has been an important topic in theoretical linguistics, as well as in applications such as speech synthesis, where accent decisions affect the naturalness as well as interpretation. Heretofore, most researchers have assumed that detailed syntactic, semantic, and discourse-level information must be available in order for accent assignment to be predicted successfully. However, a series of recent experiments on corpora of recorded (read) speech and spontaneous (elicited) speech suggest that it is indeed possible to model human accent strategies with fair success (80-98% correct) for unrestricted text --- with only the tools for automatic text analysis currently available. The algorithm developed from these experiments is currently used to assign pitch accent in the Bell Laboratories Text-to-Speech System.

This paper considers the problem of automatic assessment of local coherence. We present a novel entity-based representation of discourse which is inspired by Centering Theory and can be computed automatically from raw text. We view coherence assessment as a ranking learning problem and show that the proposed discourse representation supports the effective learning of a ranking function. Our experiments demonstrate that the induced model achieves significantly higher accuracy than a state-of-the-art coherence model. 1

I propose a model for determining the hearer's attentional state which depends solely on a list of salient discourse entities (S-list). The ordering among the elements of the S-list covers also the function of the backward-looking center in the cen- tering model. The ranking criteria for the S-list are based on the distinction between hearer-old and hearer-new discourse entities and incorporate preferences for inter- and intra-sentential anaphora. The model is the basis for an algorithm which operates incrementally, word by word.

this paper as well as the competence and interests of its author. Rather, I shall look at just one feature: how subjects differ from nonsubjects in the text. More specifically, I shall investigate the differences between subjects and nonsubjects with respect to one formal phenomenon, definiteness, and one discourse phenomenon, the information-status of the entities that the subjects and nonsubjects represent.

This paper has three aims: (1) to generalize a computational account of the discourse process called CENTERING, (2) to apply this account to discourse processing in Japanese so that it can be used in computational systems for machine translation or language understanding, and (3) to provide some insights on the effect of syntactic factors in Japanese on discourse interpretation. We argue that while discourse interpretation is an inferential process, syntactic cues constrain this process, and demonstrate this argument with respect to the interpretation of ZEROS, unexpressed arguments of the verb, in Japanese. The syntactic cues in Japanese discourse that we investigate are the morphological markers for grammatical TOPIC, the postposition wa, as well as those for grammatical functions such as SUBJECT, ga, OBJECT, o and OBJECT2, ni. In addition, we investigate the role of speaker's EMPATHY, which is the viewpoint from which an event is described. This is syntactically indicated through the use of verbal compounding, i.e. the auxiliary use of verbs such as kureta, kita. Our results are based on a survey of native speakers of their interpretation of short discourses, consisting of minimal pairs, varied by one of the above factors. We demonstrate that these syntactic cues do indeed affect the interpretation of ZEROS, but that having previously been the TOPIC and being realized as a ZERO also contributes to the salience of a discourse entity. We propose a discourse rule of ZERO TOPIC ASSIGNMENT, and show that CENTERING provides constraints on when a ZERO can be interpreted as the ZERO TOPIC