Arabic Speech Synthesis System Based on HMM

被引：6

作者：

Amrouche, Aissa ^{[1
]}

Abed, Ahcene ^{[2
]}

Falek, Leila ^{[3
]}

机构：

[1] USTHB, Lab Spoken Commun & Signal Proc, CRSTDLA, Algiers, Algeria

[2] USDB, Signal & Commun Lab, Blida, Algeria

[3] USTHB, Lab Spoken Commun & Signal Proc, Algiers, Algeria

来源：

2019 6TH INTERNATIONAL CONFERENCE ON ELECTRICAL AND ELECTRONICS ENGINEERING (ICEEE 2019) | 2019年

关键词：

text-to-speech synthesis; acoustic vectors; minimum distance; likelihood; hidden Markov models (HMM); HTS;

D O I：

10.1109/ICEEE2019.2019.00022

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The work presented in this paper is about Text-to-Speech (TTS) synthesis and, more particularly, about statistical speech synthesis using the Hidden Markov Models (HMM). The main objective of this work is to study the functioning of the HMM-based speech synthesis system (HTS) and the implementation of this method to create a system that produces understandable speech output for a given Arabic text. We have done a brief description of the statistical parametric speech synthesis based on HMM, the steps followed to implement this method for Arabic language. Finally, for the evaluations of the system are based on subjective mean opinion score and objective tests. Regarding the intelligibility, naturalness aspects (listening) and the quality (Perceptual Evaluation of Speech Quality (PESQ)).

引用

页码：73 / 78

页数：6

共 50 条

[31] The realization of speech recognition system based on HMM
Yiao, Mingming
[J]. 2008 PROCEEDINGS OF INFORMATION TECHNOLOGY AND ENVIRONMENTAL SYSTEM SCIENCES: ITESS 2008, VOL 4, 2008, : 24 - 29
[32] A Study on HMM based Speech Recognition System
Boruah, Saptarshi
Basishtha, Subhash
[J]. 2013 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND COMPUTING RESEARCH (ICCIC), 2013, : 153 - 157
[33] Robust Pitch Extraction Method for the HMM-Based Speech Synthesis System
Reddy, M. Kiran
Rao, K. Sreenivasa
[J]. IEEE SIGNAL PROCESSING LETTERS, 2017, 24 (08) : 1133 - 1137
[34] Development of an HMM-Based Speech Synthesis System for Indian English Language
Mullah, Helal Uddin
Pyrtuh, Fidalizia
Singh, L. Joyprakash
[J]. 2015 INTERNATIONAL SYMPOSIUM ON ADVANCED COMPUTING AND COMMUNICATION (ISACC), 2015, : 124 - 127
[35] A Bilingual HMM-Based Speech Synthesis System for Closely Related Languages
Justin, Tadej
Pobar, Miran
Ipsic, Ivo
Mihelic, France
Zibert, Janez
[J]. TEXT, SPEECH AND DIALOGUE, TSD 2012, 2012, 7499 : 543 - 550
[36] Design and Implementation of Burmese Speech Synthesis System Based on HMM-DNN
Liu, Mengyuan
Yang, Jian
[J]. PROCEEDINGS OF THE 2019 INTERNATIONAL CONFERENCE ON ASIAN LANGUAGE PROCESSING (IALP), 2019, : 79 - 83
[37] A Mongolian speech recognition system based on HMM
Gao, Guanglai
Biligetu
Nabuqing
Zhang, Shuwu
[J]. COMPUTATIONAL INTELLIGENCE, PT 2, PROCEEDINGS, 2006, 4114 : 667 - 676
[38] HMM Based Myanmar Text to Speech System
Thu, Ye Kyaw
Pa, Win Pa
Ni, Jinfu
Shiga, Yoshinori
Finch, Andrew
Hori, Chiori
Kawai, Hisashi
Sumita, Eiichiro
[J]. 16TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2015), VOLS 1-5, 2015, : 2237 - 2241
[39] A HMM speech recognition system based on FPGA
Ke, Sujuan
Hou, Yibin
Huang, Zhangqin
Li, Hui
[J]. CISP 2008: FIRST INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, VOL 5, PROCEEDINGS, 2008, : 305 - 309
[40] Tree-Based HMM State Tying for Arabic Continuous Speech Recognition
Azim, Mona A.
Hamid, A. Aziz A.
Badr, Nagwa L.
Tolba, M. F.
[J]. PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT SYSTEMS AND INFORMATICS 2016, 2017, 533 : 96 - 103

← 1 2 3 4 5 →