A more efficient and optimal LLR for decoding and verification

نویسندگان

  • Kwok Leung Lam
  • Pascale Fung
چکیده

We propose a new conndence score for decoding and veriication. Since the traditional log likelihood ratio (LLR) is borrowed from speaker veriication technique, it may not be apropriate for decoding because we do not have a good modelling and deenition of LLR for decoding/utterance veriication. We have proposed a new formulation of LLR that can be used for decoding and veriication task. Experimental results show that our proposed LLR can perform equally well compared with the result based on maximum likelihood in a decoding task. Also, we get an 5% improvement in decoding compared with traditional LLR.

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تاریخ انتشار 1999