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.
Arguments
df
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).
individual
whether to include individual speakers or group
them into a single Vocalisation node
...
other parameters to be passed to
getTurnTakingMatrix.
Details
Unlike 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.
See Also
(Luz, 2013) and getTurnTakingMatrix.
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.