Phonetic marking of stance in a collaborative-task spontaneous-speech corpus

While stance-taking has been examined qualitatively within conversation and discourse analysis and modeled using text-based approaches in computational linguistics, there has been little quantification of its acoustic-phonetic correlates. One reason for this is the relative sparsity of stance-taking behavior in spontaneous conversations. Another is that stance marking is embedded into a highly variable signal that encodes many other channels of information (prosody, word entropy, audience, etc.). To address these issues, we draw on varying subfields to build a corpus of stance-dense conversation and develop methods for identification and analysis of stance-related cues in the speech signal. In the corpus, dyads are engaged in three collaborative tasks designed to elicit increasing levels of investment. In these imaginary store inventory, survival, and budget-balancing scenarios, participants solve problems, but the conversation is otherwise unscripted. Based on limited previous work (Freeman, under review...