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Title: Unsupervised Phoneme Segmentation Based on Main Energy Change for Arabic Speech, Journal of Telecommunications and Information Technology, 2017, nr 1

Creator:

Lachachi, Noureddine

Date:

2017, nr 1

Resource Type:

artykuł

Description:

In this paper, a new method for segmenting speech at the phoneme level is presented. For this purpose, author uses the short-time Fourier transform of the speech signal. The goal is to identify the locations of main energy changes in frequency over time, which can be described as phoneme boundaries. A frequency range analysis and search for energy changes in individual area is applied to obtain further precision to identify speech segments that carry out vowel and consonant segment confined in small number of narrow spectral areas. This method merely utilizes the power spectrum of the signal for segmentation. There is no need for any adaptation of the parameters or training for different speakers in advance. In addition, no transcript information, neither any prior linguistic knowledge about the phonemes is needed, or voiced/unvoiced decision making is required. Segmentation results with proposed method have been compared with a manual segmentation, and compared with three same kinds of segmentation methods. These results show that 81% of the boundaries are successfully identified. This research aims to improve the acoustic parameters for all the processing systems of the Arab speech.

Publisher:

National Institute of Telecommunications

Format:

application/pdf

Resource Identifier:

ISSN 1509-4553, on-line: ISSN 1899-8852 ; oai:bc.itl.waw.pl:1963

Source:

Journal of Telecommunications and Information Technology

Language:

ang

Rights Management:

Biblioteka Naukowa Instytutu Łączności

Subject and keywords:

phoneme segmentation formant analysis energy changes band frequencies

Object collections:

Last modified:

May 11, 2017

In our library since:

May 10, 2017

Number of object content hits:

60

All available object's versions:

https://ribes-54.man.poznan.pl/publication/2240

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Edition name Date
Lachach,i Noureddine, Unsupervised Phoneme Segmentation Based on Main Energy Change for Arabic Speech, Journal of Telecommunications and Information Technology, 2017, nr 1 May 11, 2017

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