Article Type
Original Study
Abstract
The exponential expansion of data in the digital world necessitates the development of effective methods for data transmission and storage. Data compression (DC) strategies are suggested to reduce the quantity of data stored or conveyed due to constrained resources. As a result of DC ideas' ability to efficiently use existing storage space and transmission capacity, different methods have been developed in various areas. Speech coding is a lossy method of coding; therefore, the output signal differs slightly from the input signal. Speech coding is useful for message encryption, communication over long distances and speech quality. In the fields of digital voice processing and telecommunications, speech coding has been a significant problem. In this work, we demonstrate that a DCT with a chaotic system combined with a Hybrid of Huffman and Run-length coding can be utilized to implement very low bit-rate speech coding with high reconstruction quality. The proposed system was conducted on the Lbri-speech dataset and the method is evaluated based on SNR, MSE, and PSNR. The simulation results show good results and the best result was achieved with a compression ratio of about 14%. The results get MSE=0.008, SNR =34.025db, and PSNR=80.1db.
Keywords
Speech coding, Data compression, Transform coding, Neural speech coding, Speech signal
Recommended Citation
Alazawi, Sundos Abdulameer; Baker, Esraa Jaffar; and Abdulmaged, Shahbaa Mohammed
(2024)
"Speech Coding Based on a Hybrid Approach: DCT, Huffman and Run-length Coding,"
Al-Esraa University College Journal for Engineering Sciences: Vol. 6:
Iss.
9, Article 6.
DOI: https://doi.org/10.70080/2790-7732.1006
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