Research On Formants Structure In Speech Reconstruction From Chinese Whispers

Whispered speech is a special kind of speech communication.Reconstruction of normal speech from Chinese whispered speech have an important scientific value.On the other hand,it can be applied in several fields,such as the private speech communication in public,reconstruction of normal speech for the aphonic individuals,the special need for the forensic work,etc.In this dissertation,the differences between voiced sound and unvoice sound of normal speech and whispered speech are indicated,such as short-time energy,short-time average magenitude,short-time average zero-crossing rate,short-time autocorrelation function,short -time average magnitude difference function.The differences between normal speech and whispered speech are indicated in time domain.Linear Prediction Coding(LPC) is an efficient algorithm in extracting formant paremeters of speech,but it exists the questions of spurious peaks and merging peaks.It is well known that the formant spectral density is more important than the formant bandwidth.Based on the principle of pole interaction,a new LPC improved algorithm is proposed.It can extract the formants effectively by modifying the poles'radius.The experimental results show that the proposed method can extract the formants effectively,it can solve the two questions.At the same time,this algorithm is robust for noise speech. From the formants tracking curve,it can detain mean of speech formants.From them,the differences between normal speech and whispered speech are analyzed.Gaussian Mixture Model(GMM) is more robust and better performance than any other model based on mapped rules.Based on this model,a mapping rule is constructed by LSF from Chinese whispered speech to normal speech.