Open Domain Statistical Spoken Dialogue Systems |
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The aim of this project is to develop tools and techniques which
enable a spoken dialogue system to learn on-line how to sustain a
conversation about hitherto unseen concepts and topics. This includes
learning to handle new 'slots' being introduced into an existing domain
(for example, whether or not a smartphone supports contactless payment)
or the emergence of a new domain (for example, internet-connected
components for home automation). The techniques being explored are
focussed on data-driven components for understanding, dialogue
management and generation; and the key ideas centre on the use of
generic models which can be
specialised to new slots and domains, and committees of experts which
can combine knowledge from a pool of domains in order to create a
solution for a new domain.
(
EPSRC ODS-SDS Project Website)
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| Sponsor: | EPSRC |
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Statistical Spoken Dialogue Systems for Wide-Domain Applications |
| This collaborative project in co-operation with Toshiba
Cambridge Research Laboratory complements the EPSRC Open Domain SDS project
by providing an industrial relevance to the research. Particular focus is on
transfer learning from general information domains such as Tourist info to
specific product oriented domains such as Laptops and Televisions. The
research also includes work on using recurrent neural networks to build
trainable NLG.
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| Sponsor: | Toshiba |
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Robust Dialogue for Infotainment |
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The goal of this project is to develop techniques and tools which will enable
information services to be provided in-car using natural spoken language [ie not
keywords or prescribed commands] as the primary input/output modality.
The approach is based on a novel statistical framework
called the Partially Observable Markov Decision Process (POMDP).
The key benefit of the approach is that for a given level of recognition
accuracy, a POMDP-based dialogue manager can provide increased tolerance to
errors and a more natural user-oriented dialogue. The research results will
be demonstrated by a proof-of-concept server-based implementation of an
in-car tourist information service which will demonstrate both a
habitable dialogue and significantly improved robustness compared to
existing spoken dialogue technology.
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| Sponsor: | General Motors |
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Parlance: Tools for Ambient Linguistic Knowledge |
| This collaborative project was aimed at designing and building
mobile applications that approach human performance in conversational
interaction. The project involved developing an architecture to support
incremental dialogue, and advancing statistical approaches to allow dialogues
to adapt and extend to new domains.
(
Parlance Project Website)
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| Sponsor: | EU FP7: STREP |
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