Best Practices for Speech Corpora in Linguistic Research Workshop ...

6. Data analysis
Each turn is annotated by one of the following types of
tags: agr(eement), expl(anation), sugg(estion), sum(mary),
q(uestion), ch(ecking), disagr(eement), recap(itulation),
ups(hot), com(ment). These are not the exhaustive list of
tags that we are developing but here we present our analysis
using these tags only.
Figure 2: Speaker interaction
This figure, generated with Cytoscape (Smoot, Ono,
Ruscheinski, Wang and Ideker, 2011), presents a graphic
summary of the interactions between speakers. The
thickness of the edges conveys the number of occurrences
of the pair (speaker 1, speaker 2). This representation can
be understood as a probabilistic model of the meeting:
starting from one speaker, the next speaker is chosen according
to the observed frequency of turn-taking from that
speaker. The figure reveals immediately that the meeting
is dominated by four persons, Anne, Carl, Kate and Mary,
but it is also interesting to note that exchanges between
all the participants are symmetrical. Had fewer of Kate’s
turns, for example, followed those of Mary, the arrowed
edge from Mary to Kate would have been thinner than that
from Kate to Mary. Representations of this sort allow the
analyst to identify features of potential interest in the talk,
some clear (e.g. whether, for example, participants from a
particular discipline are dominating the talk or the meeting
shows evidence of cross-disciplinary exchanges), others
suggestive (e.g. in the case of unequal edges, asymmetries
in the relevant relationship).
It is also possible to complement this speaker network by
developing a representation that captures the nature of the
responses made to the prior turn. Figure 3 below provides
information about the nature of the speaker’s utterance,
given by its tag. For each edge ‘speaker 1 to speaker
2’ in the network, a corresponding bar in the figure shows
the tags that were used by speaker 2 in that turn-taking occurrence.
For example, we know from the network (figure
2) that Carl’s turns frequently follow those of Anne. The
wheel below then allows us to see at a glance that in those
40
cases roughly 10% of the responses were agreements and a
further 30% were comments, while disagreement was very
rare.
Figure 3: Speaker-Tag distribution
Having a consistent and instantly accessible way of representing
the interactions between participants will enable us
to compare different meetings and see, for example, if any
pattern emerges from a status, gender and discipline angle.
A probabilistic approach will allow us to systematise and
quantify those comparisons.
For a more general picture of relationships between pragmatic
functions, it is possible to generate a graph based on
counting the annotations for each turn in order to visualise
the frequency with which a comment follows a question for
example. This is shown in matrix form figure 4.
Figure 4: Tag pattern
Here we can see that a comment is most often followed by