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In this chapter are presented the results obtained in automatic speech recognition and understanding (ASRU) experiments made for Romanian language in the statistical framework, concerning the performance enhancement of two important knowledge resources, namely the acoustical models and the language model. If the ASRU process is for simplicity seen as a two stage process, in the first stage automatic speech recognition (ASR) is done and in the second stage the understanding is accomplished. The acoustical models incorporate knowledge about features statistic in different speech units composing the words and are mostly responsible for the performance of the recognition stage, judged after the WRR (word recognition rate). The language models incorporate knowledge about the word statistic in the phrase and determine mostly the performance of the understanding stage, judged after the PRR (phrase recognition rate). The two considered stages are interrelated and the named performance criteria are interdependent, enhanced WRR leads to PRR enhancement too. In this chapter are exposed methods to enhance the WRR, based on introducing of contextual models like triphones instead monophones or building of gender specialized models (for men, women and children) instead of global models. The methods applied to enhance the PRR are based on introducing of a restrictive finite state grammar instead the permissive word loop grammar or a bigram based language model.

Knowledge Resources in Automatic Speech Recognition and Understanding for Romanian Language