September 22-25, 1997
In this paper we describe our recent efforts to improve acoustic- phonetic modeling by developing sets of heterogeneous, phone-class- specific measurements, and combining these diverse measurements into a probabilistic classification framework. We first describe a baseline classifier using homogeneous measurements. After comparing selected sub-tasks to known human performance, we define sets of phone-class-specific measurements which improve within-class classification performance. Subsequently, we combine these heterogeneous measurements into an overall context- independent classification framework. We report on a series of phonetic classification experiments using the TIMIT acoustic-phonetic corpus. Our overall frame-work achieves 79.0% accuracy on the NIST core test set.
Bibliographic reference. Halberstadt, Andrew K. / Glass, James R. (1997): "Heterogeneous acoustic measurements for phonetic classification 1", In EUROSPEECH-1997, 401-404.