September 22-25, 1997
This paper describes a number of techniques for language verification based on acoustic processing and n-gram language modelling. A new technique is described which uses anti-models to model the general class of languages. These models are then used to normalise the acoustic score giving a 34% reduction in the error rate of the system. An approach to automatically generate discriminative subword strings for language verification is presented. The occurrence of recurrent strings are scored using a Poisson-based significance test. It is shown that when significant sub-strings do occur in the test material they are strong indicators of the target language occurring.
Bibliographic reference. Parris, Eluned S. / Lloyd-Thomas, Harvey / Carey, Michael J. / Wright, Jerry H. (1997): "Bayesian methods for language verification", In EUROSPEECH-1997, 59-62.