In order to better model pronunciation variations, we present in this paper a method to build a lexicon whose content changes dynamically with the input speech. To achieve this goal, we proceeded in two steps. In the first step, a static augmented lexicon is created by adding new phone transcriptions to a basic lexicon. These new variants are derived from phonetic features that are automatically extracted from some training speech. Then in the second step, phonetic features are extracted again during recog-nition and help to select entries in the augmented lexicon that best match the phonetic characteristics of a given speech. These selected transcriptions constitute the dynamic lexicon, which is specific to each input utterance. Experiments showed a 16.0% relative reduction in WER compared to the baseline and 16.7% compared to when a static augmented lexicon is used.
Dynamic lexicon using phonetic features
EUROSPEECH 2001, 7th European Conference on Speech Communication and Technology, September 3-7, 2001, Aalborg, Denmark
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