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- Statistical linguistic models: language models to help recognize speech,
statistics on utterance structures, on speech act detection, on utterance
sequences, etc.
- Gesture models: generation rules and gesture shapes to point at an object,
to speak, to transmit emotions, which can be applied in analysis just as well as
in generation in the case of an avatar display.
- Models linked to specific modalities: face shape bases for face tracking
and analyzing modules (emotion models, for example), lip-reading models,
writing recognition models.
- Cognitive models: human limits to take into account when generating
message, cognitive charge, attention and salience management.
- Dialogue models: possible structures, general conventions, polite turns
of speech and corresponding reactions, dialogue opening and closing patterns,
speech turn passage rules.
- Interaction models: beyond the natural language dialogue, management
models for interaction that can be oral, visual, multimodal or via MMI.
3.2.6. Assessment and scalability
InadevelopmentcycleaswehaveseeninMMI,likea V cycle [GRI96], the
tests and the assessments are not only carried out at the end of the design but
also during various stages: the development of modules leads to unitary tests,
then the integration of modules in global architecture leads to integration tests,
which then lead to global system tests, the latter allowing us to check that the
operational specifications have been followed. Finally, acceptability tests are
implemented to validate the needs analysis. We will explore the different types
of tests to be considered in MMD in Chapter 10, and we will focus here on two
specific methodological aspects: the scalability and re-implementations.
Scalability is about going from the scale of a correctly assessed laboratory
prototype to a genuine operational system usable by the public at large. The
following are the main challenges:
- Going from controlled laboratory conditions to real, variable and
uncontrollable conditions.
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