Convert a data frame into a vocalisation diagram using counts rather than sampling.
a data frame consisting, minimally, of a column for vocalisation/pause start times, a column for end times, and a column identifying the speaker, speaker role or 'Floor' (for silences).
whether to include individual speakers or group them into a single Vocalisation node
other parameters to be passed to
getSampledVocalMatrix, this function is based
on transition counts rather than sampled intervals. As a result,
where in this version self transitions will always be set to 0
(since a vocalisation by a speaker is never followed by another
vocalisation by the same speaker) in the sampled version self
transitons will usually dominate the distribution, since the
speaker who is speaking now is very likely to be the one who were
speaking one second ago.
a vocaldia object, consisting of a vocalisation matrix (vocmatrix) where cell (m,n) contains the probabilities P(n|m) transitions to node n from node m, and a table of prior probabilities (stationary distribution) per node.
(Luz, 2013) and
S. Luz. Automatic identification of experts and performance prediction in the multimodal math data corpus through analysis of speech interaction. In Proceedings of the 15th ACM on International Conference on Multimodal Interaction, ICMI'13, pages 575–582, New York, NY, USA, 2013. ACM.
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