國立虎尾科技大學 |

Source Modeling Techniques for Quality Enhancement in Statistical Parametric Speech Synthesis

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Source Modeling Techniques for Quality Enhancement in Statistical Parametric Speech Synthesis/ by K. Sreenivasa Rao, N. P. Narendra.
作者:	Rao, K. Sreenivasa.
其他作者:	Narendra, N. P.
面頁冊數:	XII, 136 p. 74 illus., 11 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Signal processing. -
電子資源:	https://doi.org/10.1007/978-3-030-02759-9
ISBN:	9783030027599

Source Modeling Techniques for Quality Enhancement in Statistical Parametric Speech Synthesis
Rao, K. Sreenivasa.

Source Modeling Techniques for Quality Enhancement in Statistical Parametric Speech Synthesis[electronic resource] /by K. Sreenivasa Rao, N. P. Narendra. - 1st ed. 2019. - XII, 136 p. 74 illus., 11 illus. in color.online resource. - SpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning,2191-737X. - SpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning,.

Chapter 1. Introduction -- Chapter 2. Background and literature review -- Chapter 3. Robust voicing detection and F0 estimation method -- Chapter 4. Parametric approach of modeling the source signal -- Chapter 5. Hybrid approach of modeling the source signal -- Chapter 6. Generation of creaky voice -- Chapter 7. Summary and conclusions.

This book presents a statistical parametric speech synthesis (SPSS) framework for developing a speech synthesis system where the desired speech is generated from the parameters of vocal tract and excitation source. Throughout the book, the authors discuss novel source modeling techniques to enhance the naturalness and overall intelligibility of the SPSS system. This book provides several important methods and models for generating the excitation source parameters for enhancing the overall quality of synthesized speech. The contents of the book are useful for both researchers and system developers. For researchers, the book is useful for knowing the current state-of-the-art excitation source models for SPSS and further refining the source models to incorporate the realistic semantics present in the text. For system developers, the book is useful to integrate the sophisticated excitation source models mentioned to the latest models of mobile/smart phones. Presents the efficient excitation source modeling techniques for generating high quality speech; Includes a combination of both waveform and parametric methods to enhance the quality of synthesis; Features and methods that need less memory and computational requirements than others, allowing them to be integrated to smart phones and smaller devices.

ISBN: 9783030027599

Standard No.: 10.1007/978-3-030-02759-9doiSubjects--Topical Terms:

561459
Signal processing.

LC Class. No.: TK5102.9

Dewey Class. No.: 621.382

Source Modeling Techniques for Quality Enhancement in Statistical Parametric Speech Synthesis
LDR:03211nam a22004215i 4500 001 1004281
003 DE-He213
005 20200705150228.0
007 cr nn 008mamaa
008 210106s2019 gw | s |||| 0|eng d
020 $a 9783030027599 $9 978-3-030-02759-9
024 7 $a 10.1007/978-3-030-02759-9 $2 doi
035 $a 978-3-030-02759-9
050 4 $a TK5102.9
050 4 $a TA1637-1638
072 7 $a TTBM $2 bicssc
072 7 $a TEC008000 $2 bisacsh
072 7 $a TTBM $2 thema
072 7 $a UYS $2 thema
082 0 4 $a 621.382 $2 23
100 1 $a Rao, K. Sreenivasa. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 891982
245 1 0 $a Source Modeling Techniques for Quality Enhancement in Statistical Parametric Speech Synthesis $h [electronic resource] / $c by K. Sreenivasa Rao, N. P. Narendra.
250 $a 1st ed. 2019.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a XII, 136 p. 74 illus., 11 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a SpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning, $x 2191-737X
505 0 $a Chapter 1. Introduction -- Chapter 2. Background and literature review -- Chapter 3. Robust voicing detection and F0 estimation method -- Chapter 4. Parametric approach of modeling the source signal -- Chapter 5. Hybrid approach of modeling the source signal -- Chapter 6. Generation of creaky voice -- Chapter 7. Summary and conclusions.
520 $a This book presents a statistical parametric speech synthesis (SPSS) framework for developing a speech synthesis system where the desired speech is generated from the parameters of vocal tract and excitation source. Throughout the book, the authors discuss novel source modeling techniques to enhance the naturalness and overall intelligibility of the SPSS system. This book provides several important methods and models for generating the excitation source parameters for enhancing the overall quality of synthesized speech. The contents of the book are useful for both researchers and system developers. For researchers, the book is useful for knowing the current state-of-the-art excitation source models for SPSS and further refining the source models to incorporate the realistic semantics present in the text. For system developers, the book is useful to integrate the sophisticated excitation source models mentioned to the latest models of mobile/smart phones. Presents the efficient excitation source modeling techniques for generating high quality speech; Includes a combination of both waveform and parametric methods to enhance the quality of synthesis; Features and methods that need less memory and computational requirements than others, allowing them to be integrated to smart phones and smaller devices.
650 0 $a Signal processing. $3 561459
650 0 $a Image processing. $3 557495
650 0 $a Speech processing systems. $3 564428
650 0 $a Natural language processing (Computer science). $3 802180
650 0 $a Computational linguistics. $3 555811
650 1 4 $a Signal, Image and Speech Processing. $3 670837
650 2 4 $a Natural Language Processing (NLP). $3 1254293
650 2 4 $a Computational Linguistics. $3 670080
700 1 $a Narendra, N. P. $e author. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1297715
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783030027582
776 0 8 $i Printed edition: $z 9783030027605
830 0 $a SpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning, $x 2191-737X $3 1255129
856 4 0 $u https://doi.org/10.1007/978-3-030-02759-9
912 $a ZDB-2-ENG
912 $a ZDB-2-SXE
950 $a Engineering (SpringerNature-11647)
950 $a Engineering (R0) (SpringerNature-43712)