Title :
An Efficient Network for Farsi Text to Speech Conversion Using Vowel State
Author :
Rasekh, Ehsan ; Eshghi, Mohammad
Author_Institution :
Electr. & Comput. Eng. Fac., Shahid Beheshti Univ., Tehran
Abstract :
The main problem in Farsi text to speech synthesizers is unwritten short vowels in Farsi orthography. In this paper an ANN is used to determine the phonemes in a Farsi text. The output of this ANN is a new variable called vowel state, instead of a phoneme. Five vowel states are enough to extract pronunciations in a Farsi text, where the number of phonemes is about 30. This reduction of the output causes the reduction of interconnections of the network, considerably. The proposed vowel states approach and the ANN is tested over 2024 words with different percentage of the database as the training set. The 80.31% to 97.34% correct results are achieved using this system
Keywords :
learning (artificial intelligence); natural languages; neural nets; speech processing; speech synthesis; ANN; Farsi orthography; artificial neural network; phoneme; pronunciation extraction; text to speech synthesis; training set; vowel state approach; Artificial neural networks; Computer networks; Dictionaries; Helium; Natural languages; Optical computing; Silicon compounds; Speech synthesis; Synthesizers; Testing;
Conference_Titel :
TENCON 2006. 2006 IEEE Region 10 Conference
Conference_Location :
Hong Kong
Print_ISBN :
1-4244-0548-3
Electronic_ISBN :
1-4244-0549-1
DOI :
10.1109/TENCON.2006.343934
