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

a) b) c)
Figure 6: Web experiment on regional variation of speech sounds in German using the Percy software. a) registration web
form, b) experiment item screen, c) final display of geographic distribution of recordings.
3. Data exchange with tools with different underlying
data models may require manual adaptation.
4. It is debatable whether SQL is a suitable query language
for phoneticians or linguists, and whether it is
sufficiently powerful to express typical research questions.
5.1. Missing data
Missing data can be controlled by enforcing a minimum
standard set of metadata and log data to be collected during
the speech database creation. However, this may not
be feasible when the speech database comes from an external
partner. It is thus necessary to manually check external
databases before incorporating them into the WikiSpeech
system, and to document the data manipulations applied.
Database systems provide a default null value for unknown
data, which at least ensures that queries can be run. If
queries return unexpected results, then default null data
maybe the reason for this. In a relational database the
database schema can be inspected either via queries or via
a graphical user interface, and thus it is in general quite
straightforward to find out whether missing data is a possible
reason for unexpected query results.
5.2. Incorporating new tools
A database schema is intended to remain stable over time
so that predefined views, proceduralized queries or scripts
continue to work. However, new tools and services may use
data items not present in the database. If the new data cannot
be represented the given database schema, this schema
has to be extended. In general, simply extending the data
model, e.g. by adding new attributes in the relation tables,
or even adding new tables, is not critical. Critical changes
include changing the relationships between data items, or
removing attributes or relational tables. Such changes however
will be very rare because the data model has reached a
very stable state by now.
Any change to the data model can only be performed by the
database administrator, and it may entail the modification
of existing scripts and queries.
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5.3. Manual adaption of data
For tools that use a different underlying data model, any
data that is exported to the tool and then reimported must
be processed to minimize the loss of information. For example,
in a data model that uses symbolic references between
elements on different annotation tiers, all items must
be given explicit time stamps and unique ids to be used in a
purely time-based annotation tool such as e.g. Praat. Upon
reimporting the data after processing in Praat, these timestamps
have to be removed for non time-aligned annotations.
Such modifications are in generally implemented using
a parameterized import and export script. Several such
scripts may be necessary for the different tools used in the
workflow.
5.4. SQL as a query language
SQL is the de facto standard query language for relational
databases. However, it is quite verbose and lacks many
of the operators needed in phonetic or linguistic research,
namely sequence and dominance operators. Both sequence
and dominance operators can be expressed by providing explicit
position attributes or linking relations between data
records, but they make queries even longer and more complex.
The SQL view mechanism is a simple way of formulating
simple queries. For example, in the web experiment, where
experiment setup and input spread over 8 relational tables,
a single view contains all data fields of the experiment and
appears to the user as one single wide table, which can be
directly imported into R or Excel.
As an alternative to the direct use of SQL, high-level application
domain specific query languages can be envisaged,
which are then automatically translated to SQL for
execution. This separation of high-level query language
and the SQL query evaluation is desirable, because it opens
the possibility to provide many different query language to
the same underlying database. Such query languages can
be text-based or graphical, very specific to a particular application
domain or quite abstract. In fact, many graphical
front-ends to database systems already allow form-like
query languages or explorative interactive graphical query
languages.