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

is often fluid in terms of communicative goals. Corpus
compilers have tackled classification in slightly differing
manners and levels of granularity. While BNC lumps casual
conversation a single category, the Cambridge and
Nottingham Corpus of Discourse in English (CANCODE)
differentiates such speech events along two axes: the
relational and goal dimensions (McCarthy, 1998:5). One
problem with this scheme is the rigid divide it proposes for
goal classification and in some cases for speaker relations.
Conversations in real life may be either task or idea oriented
at different specific times (Gu, 2010) or include differing
social relations within the same situated discourse. One way
of resolving the multi-dimensionality and fluidity of
discourse in corpus files would be to include social activity
types in metadata.
The discussion above has raised a number of issues in
spoken corpus compilation, focusing on certain design
features. In the following, we highlight aspects of speaker
demographics, and the employment of domain and social
activity criteria for genre classification, which is
supplemented with discourse topic and speech act
annotation in metadata.
3. Corpus Design, Pragmatic Metadata, and
Sampling Procedures in STC and STCDC
The construction of STC and STCDC as web-based corpora
started at different but close times at the campuses of Middle
East Technical University in Ankara and Güzelyurt (in 2008
and 2010, respectively; http://www.stc.org.tr/en/;
http://corpus.ncc.metu.edu.tr/? lang=en). STC will function
as a general corpus for spoken Turkish in Turkey. It thus is a
Variety corpus that includes demographic variation and
different genres. STCDC is also a Variety corpus that
includes different genres, but it has a regional dialect slant.
Despite the dialectal focus of STCDC, the two corpora may
be used for variation analysis because their sampling frames
are similar and because they employ the same speaker
metadata and genre classification parameters (see Andersen,
2010: 557).
With respect to speaker metadata, both STC and STCDC
include standard demographic categories such as place of
birth and residence, age, education, etc. In addition to these,
speakers are described according to length of residence in
different geographical locations (see Ruhi et al. (2010c) for
a fuller description of the metadata features in STC). Both
corpora also document the language profiles of the speakers.
This will allow sifting of speakers according to these
parameters in future dialect research.
STC and STCDC employ two parameters in genre
classification: speaker relations and social activity type. The
major domains are family, friend, family-friend, educational,
service encounter, workplace, media discourse, legal,
political, public, research, brief encounter, and unclassified.
Finer granularity in metadata is achieved during the corpus
assignment and the various steps in the transcription stage in
STC through annotation of speech acts (e.g. criticizing), on
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the one hand, and on the other hand, annotation for
conversational topics (e.g. child care), speech events (e.g.
troubles talk), and ongoing social activities (e.g., cooking).
In the current state of STC, speech acts are annotated as a
separate category from topic annotation categories, but
Topics as a super-category includes local conversational
topics and discoursal topics, which, as evident in the
examples given above, concern the meso-level of discourse
in that they are more discourse activities than topics in the
strict sense (see Levinson (1979) on activity types).
The inclusion of speech acts and topics as two further
parameters in metadata is motivated by the assumption that
combining generic metadata with more specific pragmatic
annotation renders corpora more ‘visible’ for pragmatics
research, broadly construed here to include variation
analysis. Conflating local and global topics in a single
category may not be the ideal route. However, given that
speech event, activities and discoursal topic categorizations
are fuzzy notions, 1 we submit that separating them from
local topics would not add to the worth of the annotation
(Speech act and topic annotation will be implemented in
STCDC Project at a later stage.). Figure 1 is a partial display
of the metadata for a file in STC:
Figure 1. Partial metadata for a communication in STC
This metadata annotation design is an improvement for
pragmatics-oriented research on spoken corpora, where
scholars have underscored the difficulty of retrieval of
speech act realizations through standard searches that more
often than not rely on the extant literature on speech acts in
various languages (see, e.g., Jucker et al. (2008) for an
investigation of compliments in BNC). Identifying speech
act realizations during the corpus construction stage can
enhance corpus-driven approaches to pragmatics (broadly
construed here to include variation analysis) by providing
starting points for researchers on where to look for the
relevant realizations in the ‘jungle’ of corpus data. As has
been noted scholars that critically assess the possibility of
doing corpus-oriented discourse analysis and pragmatics
1
See Adolphs, Knight & Carter (2011) for related remarks on
classifying activities in corpus.