Parameterizing Speech Phonemes by Exponential Sinusoidal Model
نویسندگان
چکیده
The exponential sinusoidal model (ESM) for parameterizing speech signals is proposed in this paper. The main feature of the ESM is that the amplitude of each sinusoidal component is allowed to vary exponentially with time. A novel variable segmentation strategy is applied first to separate individual transients of a voiced phoneme, which can then be fitted with the ESM. The epoch of a transient is used to separate each speech segment, and the estimation of the ESM parameters is carried out by utilizing the accumulated autocorrelation functions (AACFs) of the speech segment. It is demonstrated that the proposed epoch-ESM representation can be used in analysis-synthesis of voiced phonemes with high accuracy and low computational complexity.
منابع مشابه
Exponential sinusoidal modeling of transitional speech segments
A generalized sinusoidal model for speech signal processing is studied. The main feature of the model is that the amplitude of each sinusoidal component is allowed to vary exponentially with time. We propose to use the model in transitional speech segments such as speech onsets and voiced/unvoiced transitions. Computer simulations with natural speech signals indicate substantial better modeling...
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