Automatic Mapping Clinical Notes to Medical - RMIT University

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$journal of latex class files, vol. 6, no. 1, january ... - RMIT University$

The principles are dichotomous — each can take the value of speaker or other (other interlocutor) — and thus define eight mutually exclusive VRM categories, as shown in Table 1. With 8 VRM modes and 2 separate dimensions of coding (literal and pragmatic meaning), there are 64 possible form-intent combinations. The 8 combinations of codings in which the literal and pragmatic meanings coincide are referred to as pure modes. The other 56 modes are labelled mixed modes. An example of a mixed-mode utterance is “Can you pass the sugar?” which is coded QA. This is read Question in service of Advisement, meaning that the utterance has a Question form (literal meaning) but Advisement intent (pragmatic meaning). In this way, the VRM taxonomy is designed to simply and consistently classify and distinguish direct and indirect speech acts. 4 Comparison with Other Speech Act Taxonomies There are, of course, alternate speech and dialogue act taxonomies, some of which have been applied within natural language processing applications. Unfortunately, many of these taxonomies tend to offer competing, rather than complementary approaches to classifying speech acts, making it difficult to compare experimental results and analyses that are based on different taxonomies. It would clearly be desirable to unambiguously relate categories between different taxonomies. One specific drawback of many speech and dialogue act taxonomies, including taxonomies such as those developed in the VERBMOBIL project (Alexandersson et al., 1998), is that they are domain or application specific in their definition and coverage of speech act categories. This often stems from the taxonomy being developed and used in a rather ad hoc, empirical manner for analysing discourse and utterances from a single or small set of application domains. While the VRM research grew from studying therapist interventions in psychotherapy (Stiles, 1992; Wiser and Goldfried, 1996), the VRM system has been applied to a variety of discourse genres. These include: American Presidential speeches (Stiles et al., 1983), doctor-patient interactions (Meeuswesen et al., 1991), courtroom interrogations (McGaughey and Stiles, 1983), business negotiations (Ulijn and Verweij, 2000), persuasive discourse (Kline et al., 1990) and tele- 34 vision commercials (Rak and McMullen, 1987). VRM coding assumes only that there is a speaker and an intended audience (other), and thus can be applied to any domain of discourse. The wide applicability of VRM is also due to its basis of clearly defined, domain-independent, systematic principles of classification. This ensures that the VRM categories are both extensive and exhaustive, meaning that all utterances can be meaningfully classified with exactly one VRM category 1 . In contrast, even widely-applied, complex taxonomies such as DAMSL (Core and Allen, 1997) resort to the inclusion of an other category within the speech act component, to be able to classify utterances across domains. In addition, the VRM principles facilitate more rigorous and comparable coding of utterances from which higher-level discourse properties can be reliably calculated, including characterisation of the roles played by discourse participants. If required, the eight VRM modes can also be further divided to identify additional features of interest (for example, the Question category could be split to distinguish open and closed questions). Importantly, this can be done within the existing framework of categories, without losing the principled basis of classification, or the ability to compare directly with other VRM analyses. Table 2 compares the VRM categories with Searle’s five major speech act categories (1969; 1979). Searle’s categories are largely subsumed under the subset of VRM categories that offer the speaker’s source of experience and/or frame of reference (Disclosure, Edifications, Advisements and Questions). The coverage of Searle’s speech acts seems more limited, given that the other VRMs (Reflection, Interpretation, Confirmation and Acknowledgement), all other on at least two principles, have no direct equivalents in Searle’s system, except for some Interpretations which might map to specific subcategories of Declaration. 5 Building a VRM Classifier As discussed earlier, the VRM system codes both the literal and pragmatic meaning of utterances. The pragmatic meaning conveys the speaker’s actual intention, and such meaning is often hidden or 1 The only exceptions are utterances that are inaudible or incomprehensible in spoken dialogue, which are coded Uncodable (U).
Source of Presumption Frame of VRM Description Experience about Reference Mode Experience Speaker Speaker Speaker Disclosure (D) Reveals thoughts, feelings, perceptions or intentions. E.g., I like pragmatics. Other Edification (E) States objective information. E.g., He hates pragmatics. Other Speaker Advisement (A) Attempts to guide behaviour; suggestions, commands, permission, prohibition. E.g., Study pragmatics! Other Confirmation (C) Compares speaker’s experience with other’s; agreement, disagreement, shared experience or belief. E.g., We both like pragmatics. Other Speaker Speaker Question (Q) Requests information or guidance. E.g., Do you like pragmatics? Other Acknowledgement (K) Conveys receipt of or receptiveness to other’s communication; simple acceptance, salutations. E.g., Yes. Other Speaker Interpretation (I) Explains or labels the other; judgements or evaluations of the other’s experience or behaviour. E.g., You’re a good student. Other Reflection (R) Puts other’s experience into words; repetitions, restatements, clarifications. E.g., You dislike pragmatics. Table 1: The Taxonomy of Verbal Response Modes from (Stiles, 1992) Searle’s Classification Corresponding VRM Commissive Disclosure Expressive Disclosure Representative Edification Directive Advisement; Question Declaration Interpretation; Disclosure; Edification Table 2: A comparison of VRM categories with Searle’s speech acts highly dependent on discourse context and background knowledge. Because we classify utterances using only intra-utterance features, we cannot currently encode any information about the discourse context, so could not yet plausibly tackle the prediction of pragmatic meaning. Discerning literal meaning, while somewhat simpler, is 35 akin to classifying direct speech acts and is widely recognised as a challenging computational task. 5.1 Corpus of VRM Annotated Utterances Included with the VRM coding manual (Stiles, 1992) is a VRM coder training application for training human annotators. This software, which is freely available online 2 , includes transcripts of spoken dialogues from various domains segmented into utterances, with each utterance annotated with two VRM categories that classify both its literal and pragmatic meaning. These transcripts were pre-processed to remove instructional text and parenthetical text that was not actually part of a spoken and coded utter- 2 The VRM coder training application and its data files are available to download from http://www.users.muohio.edu/stileswb/archive.htmlx
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