Sixth International Conference on Spoken Language Processing
October 16-20, 2000
Dynamic Adaptation of Vocabulary Independent HMMs to an Application Environment
Claudio Vair (1), Luciano Fissore (1), Pietro Laface (2)
(1) CSELT - Centro Studi e Laboratori Telecomunicazioni,
The paper presents a software architecture allowing to collect, select,
and exploit speech data from a specific application field to
dynamically generate Hidden Markov Models tailored to that application
environment and vocabulary.
The framework we are interested in is, therefore, an already operational
voice activated service that allows to collect directly from
the field a large amount of speech data.
We propose a procedure for data selection and for incremental
training of the units using a strategy of model selection.
Several tests are presented for a train timetable information system,
and for a Directory Assistance application with a very large
vocabulary of city names showing that significant improvements
can be obtained with respect to the laboratory models, keeping the
old models and transcribing only the most frequent words in terms
of the new units, incrementally trained from the field data.
(2) Dipartimento di Automatica e Informatica - Politecnico di Torino,
Vair, Claudio / Fissore, Luciano / Laface, Pietro (2000):
"Dynamic adaptation of vocabulary independent HMMs to an application environment",
In ICSLP-2000, vol.2, 839-842.