getSampledVocalCountMatrix | R Documentation |
Generate a count vocalisation diagram through 'sampling'.
getSampledVocalCountMatrix( cdf, rate = 1, individual = FALSE, noPauseTypes = FALSE, begin = "begin", end = "end", nodecolumn = "role" )
cdf |
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). |
rate |
the rate at which to sample the vocalisation events (in seconds) |
individual |
whether to include individual speakers or group them into a single Vocalisation node |
noPauseTypes |
if TRUE, ignore distinctions between pauses (SwitchingPause, GrpSwitchingPause, etc) |
begin |
the name of the column containing the start time of the vocalisation event in a row. |
end |
the name of the column containing the end time of the vocalisation event in the same row. |
nodecolumn |
the name of the column containing the node (speaker) name (e.g. 'speaker', 'role'). |
A vocalisation diagram (vocaldia) is a representation of a dialogue as a Markov process whose cell <m,n> contains the transition probability from node n to node m). This function for 'cases' (an identifier for a case or a vector of identifiers identifying a set of cases) in data frame 'df', obtained by sampling the timeline every 'rate'-th second (see getSampledVocalCountMatrix).
a vocaldia object, consisting of a vocalisation matrix (vocmatrix) where cell <m,n> contains the counts of transitions from node n to node m, and a table of prior probabilities (stationary distribution) per node.
(Luz, 2013)
data(vocdia) getSampledVocalCountMatrix(subset(atddia, id=='Abbott_Maddock_01'), nodecolumn='role')
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