getSampledVocalCountMatrix {vocaldia}

getSampledVocalCountMatrix: generate vocalisation diagrams

Description

Generate a count vocalisation diagram through 'sampling'.

Usage

getSampledVocalCountMatrix(
  cdf,
  rate = 1,
  individual = FALSE,
  noPauseTypes = FALSE,
  begin = "begin",
  end = "end",
  nodecolumn = "role"
)

Arguments

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').

Details

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).

Value

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.

See Also

(Luz, 2013)

Examples

data(vocdia) 
getSampledVocalCountMatrix(subset(atddia,
     id=='Abbott_Maddock_01'), nodecolumn='role')