Development of high quality speech compression system for Quranic recitation based on modified CELP algorithm
Teddy Surya Gunawan, Mira Kartiwi
Abstract
Teddy Surya Gunawan, Mira Kartiwi
Abstract
Currently, there are more than 500 Quranic recitations available freely on the internet. There is also a growing trends on the use of smart phone compare to traditional desktop PCs for accessing the internet. On such limited device, a high quality speech compression for Quranic recitation is favorable. In this paper, we developed a high quality speech compression for Quranic recitation by modifying Code Excited Linear Prediction (CELP) algorithm. First, the characteristics of the Quranic recitation of all surahs was evaluated in which it was found that the voiced speech is more dominant compare to unvoiced speech. Next, we optimize CELP algorithm based on previous findings by modifying the original stochastic codebook. Instead of random Gaussian signal, we trained the codebook using LBG algorithm for Surah Al-Fatihah, and used the trained codebook for the whole Quran. Lastly, we evaluate the performance of the developed algorithm objectively using PESQ (Perceptual Evaluation of Speech Quality). Results showed that our proposed algorithm performs better than the traditional CELP algorithm, in terms of PESQ score and processing time.
OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Currently, there are more than 500 Quranic recitations available freely on the internet. There is also a growing trends on the use of smart phone compare to traditional desktop PCs for accessing the internet. On such limited device, a high quality speech compression for Quranic recitation is favorable. In this paper, we developed a high quality speech compression for Quranic recitation by modifying Code Excited Linear Prediction (CELP) algorithm. First, the characteristics of the Quranic recitation of all surahs was evaluated in which it was found that the voiced speech is more dominant compare to unvoiced speech. Next, we optimize CELP algorithm based on previous findings by modifying the original stochastic codebook. Instead of random Gaussian signal, we trained the codebook using LBG algorithm for Surah Al-Fatihah, and used the trained codebook for the whole Quran. Lastly, we evaluate the performance of the developed algorithm objectively using PESQ (Perceptual Evaluation of Speech Quality). Results showed that our proposed algorithm performs better than the traditional CELP algorithm, in terms of PESQ score and processing time.
Key concepts: Code-excited linear prediction, PESQ, Codebook, Computer science, Speech coding, Speech recognition, Linear predictive coding, Vector sum excited linear prediction