Eight oligonucleotide fragments were designed with the aid of a computer and synthesizedaccording to the amino add sequcnce of human atrial natriuretic factor(ANF).By means of an-nealing and ligation,these fragments w...Eight oligonucleotide fragments were designed with the aid of a computer and synthesizedaccording to the amino add sequcnce of human atrial natriuretic factor(ANF).By means of an-nealing and ligation,these fragments were assembled into an overlapping concatenator consisting oftwo ANF genes ligated by TGATG for termination and initiation of translation.Theconcatenator was omserted into plasmid pRC23 and the recobinant DNA was transformed into E.coli strain TAP106.Analysis by restriction enzyme mapping,hybridization and DNA sequenongshowed that the orientation and reading frame of the gene were correct.展开更多
This paper proposes a trainable unit selection speech synthesis method based on statistical modeling framework. At training stage, acoustic features are extracted from the training database and statistical models are ...This paper proposes a trainable unit selection speech synthesis method based on statistical modeling framework. At training stage, acoustic features are extracted from the training database and statistical models are estimated for each feature. During synthesis, the optimal candidate unit sequence is searched out from the database following the maximum likelihood criterion derived from the trained models. Finally, the waveforms of the optimal candidate units are concatenated to produce synthetic speech. Experiment results show that this method can improve the automation of system construction and naturalness of synthetic speech effectively compared with the conventional unit selection synthe-sis method. Furthermore, this paper presents a minimum unit selection error model training criterion according to the characteristics of unit selection speech synthesis and adopts discriminative training for model parameter estimation. This criterion can finally achieve the full automation of system con-struction and improve the naturalness of synthetic speech further.展开更多
文摘Eight oligonucleotide fragments were designed with the aid of a computer and synthesizedaccording to the amino add sequcnce of human atrial natriuretic factor(ANF).By means of an-nealing and ligation,these fragments were assembled into an overlapping concatenator consisting oftwo ANF genes ligated by TGATG for termination and initiation of translation.Theconcatenator was omserted into plasmid pRC23 and the recobinant DNA was transformed into E.coli strain TAP106.Analysis by restriction enzyme mapping,hybridization and DNA sequenongshowed that the orientation and reading frame of the gene were correct.
基金Supported by the National Natural Science Foundation of China (Grant Nos. 60475015, 60610298) National Hi-Tech Research and Development Program of China (Grant Nos. 2006AA01Z137 and 2006AA010104)
文摘This paper proposes a trainable unit selection speech synthesis method based on statistical modeling framework. At training stage, acoustic features are extracted from the training database and statistical models are estimated for each feature. During synthesis, the optimal candidate unit sequence is searched out from the database following the maximum likelihood criterion derived from the trained models. Finally, the waveforms of the optimal candidate units are concatenated to produce synthetic speech. Experiment results show that this method can improve the automation of system construction and naturalness of synthetic speech effectively compared with the conventional unit selection synthe-sis method. Furthermore, this paper presents a minimum unit selection error model training criterion according to the characteristics of unit selection speech synthesis and adopts discriminative training for model parameter estimation. This criterion can finally achieve the full automation of system con-struction and improve the naturalness of synthetic speech further.
