Multilayer Analysis of Conflictive Conversational Speech Using the Computational Tool OralStats Furious
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Abstract
This research explores some prosodic features of discursive conflict, based on the manual and automatic analysis of 1371 intonational groups from 7 conversations within the same family. Out of these, 738 were manually designated as non-conflictive, while 633 were labeled as conflictive. Statistical tools, including ANOVA and boxplots, have helped clarify singularities inherent to discursive conflict. The research focuses on the examination of tone, revealing significant disparities both among speakers and in conflict contexts. Despite general consistency in the data, notable variations are observed, especially in the case of a particular speaker whose tone shows remarkable variability between conflictive and non-conflictive sequences. Importantly, speech rate emerged as a distinctive prosodic marker, showing significant differences both among speakers and in conflict scenarios. In contrast, variables such as tonal inflection, intensity, and duration did not show significant differences based on conflict levels or speaker identities, suggesting the need for precise and contextualized analysis. The creation and development of the Oralstats Furious program for automatic categorization introduced an additional layer to the study. Discrepancies between manual and automatic categorizations revealed significant disparities, hinting at possible overestimations or underestimations of conflict in manual analyses. Interactive data visualization proved invaluable for accurate validation, allowing researchers to refine both manual and automatic classifications.
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Funding data
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Ministerio de Ciencia e Innovación
Grant numbers MCIN/AEI /10.13039/501100011033
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