An algorithm for speech parameter generation from continuous mixture HMMs with dynamic features
نویسندگان
چکیده
This paper proposes an algorithm for speech parameter generation from continuous mixture HMMs which include dynamic features, i.e., delta and delta-delta parameters of speech. We show that the parameter generation from HMMs using the dynamic features results in searching for the optimal state sequence and solving a set of linear equations for each possible state sequence. To solve the problem, we derive a fast algorithm on the analogy of the RLS algorithm for adaptive ltering. We show that the generated speech parameter vectors re ect not only the means of static and dynamic feature vectors but also the covariances of those. An example presenting e ectiveness of the proposed algorithm in speech synthesis is given.
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