In this framework, the sources of variability are modeled in different manners. Context-dependent phoneme models, such as diphones and triphones, are used to account for coarticulation between consecutive phonemes. Spectral variability of the same phoneme sequence arising from different speakers or recording conditions is generally represented by using a mixture of Gaussians to cover the acoustic feature space. One of our objectives is to increase our understanding of the main sources of variability found in the speech signal and thus improve our ability to model the wide spectrum of allophonic variants. We base our investigations on very large speech corpora, enabling continual assessment of our acoustic modeling capability of the observed allophonic variants.
Variability arising from fast speaking rates is the least well accounted for.
Different possible research directions include the use of different acoustic-phonetic units, the use of compound words for frequent word sequences, and the use of specific phonological rules for fast speech. In the context of our work on spoken language understanding systems, where users interact with a machine in order to carry out an information retrieval task, we study the characteristics of spontaneous speech. In addition to the above mentioned sources of variability, other events are frequent, including hesitations, breath noises, word fragments, as well as large variations in speaking rate and segment duration within the same sentence. Specific acoustic models are used for breath noises and hesitations in spontaneous speech. These models are similar to the silence models used in recognition of read texts, as they complete the acoustic modeling but do not correspond to lexical items.