Hybrid Connectionist-structural Acoustical Modeling
نویسنده
چکیده
In this paper, we introduce several hybrid connectionist-structural acoustic models for context-independent phone-like units. The structural part has been modeled with Markov chains or nite state networks learned by grammatical inference techniques. A multilayer perceptron or a committee of multilayer perceptrons is used to estimate the emission probabilities of the structural models. We compare the recognition performance attained by these models with the performance obtained by classical continuous density hidden Markov models for context-independent and context-dependent units on an acoustic-phonetic decoding task and on a semantic restricted task.
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