This paper deals with an inter-annotator agreement test involving the identification of the information unit of Topic as defined within the framework of the Language into Act Theory (L-AcT). Fleiss’s kappa statistic was used to measure the agreement among the four annotators who took part in the test. The data used was sampled from C-ORAL-BRASIL II, a spontaneous speech corpus of Brazilian Portuguese. The paper begins by outlining of the theoretical underpinnings of L-AcT, dedicating special attention to aspects directly related to the notion of Topic. Section 2 presents the pilot test and discusses methodological and theoretical issues that were relevant for the design of the protocol that was eventually used in the actual test. Sections 3 and 4 deal with the test, its protocol and results (the kappa coefficient for the general agreement was 0.79, which by usual standards represents a substantial agreement). Section 5 first provides a brief review of a few studies conducted according to other frameworks which have dealt with inter-rater agreement on the annotation of information structure categories. Finally, the errors observed in the test are analyzed qualitatively.

This paper presents the American English (AE) minicorpus, a spontaneous speech resource created within the auspices of the C-ORAL-BRASIL project consisting of texts selected from the Santa Barbara Corpus of Spoken American English. We focus on the sampling strategy that guided the selection of texts, the transcription criteria that were implemented and the prosodic and informational annotation carried on the AE minicorpus. The minicorpus was designed to be comparable to the minicorpora of the C-ORAL projects for Italian and Brazilian Portuguese, which were conceived to allow the study of information structure in spontaneous speech in accordance with the principles of the Language into Act Theory. This theory comprises a pragmatic framework for the study of spontaneous speech and it integrates the IPO approach into its prosodic model. The IPO approach consists of a perception-based model for the study of intonation, providing an apparatus for the description and classification of melodic contours observed in spontaneous speech.

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