کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
535245 870334 2007 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A new look at discriminative training for hidden Markov models
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
A new look at discriminative training for hidden Markov models
چکیده انگلیسی

Discriminative training for hidden Markov models (HMMs) has been a central theme in speech recognition research for many years. One most popular technique is minimum classification error (MCE) training, with the objective function closely related to the empirical error rate and with the optimization method based traditionally on gradient descent. In this paper, we provide a new look at the MCE technique in two ways. First, we develop a non-trivial framework in which the MCE objective function is re-formulated as a rational function for multiple sentence-level training tokens. Second, using this novel re-formulation, we develop a new optimization method for discriminatively estimating HMM parameters based on growth transformation or extended Baum–Welch algorithm. Technical details are given for the use of lattices as a rich representation of competing candidates for the MCE training.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pattern Recognition Letters - Volume 28, Issue 11, 1 August 2007, Pages 1285–1294
نویسندگان
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