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

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