Audio Compression using a Modified Vector Quantization algorithm for Mastering Applications

Shajin Prince, Bini D, Alfred Kirubaraj A, Samson Immanuel J, Surya M


Audio data compression is used to reduce the transmission bandwidth and storage requirements of audio data. It is the second stage in the audio mastering process with audio equalization being the first stage. Compression algorithms such as BSAC, MP3 and AAC are used as standards in this paper. The challenge faced in audio compression is compressing the signal at low bit rates. The previous algorithms which work well at low bit rates cannot be dominant at higher bit rates and vice-versa. This paper proposes an altered form of vector quantization algorithm which produces a scalable bit stream which has a number of fine layers of audio fidelity. This modified form of the vector quantization algorithm is used to generate a perceptually audio coder which is scalable and uses the quantization and encoding stages which are responsible for the psychoacoustic and arithmetical terminations that are actually detached as practically all the data detached during the prediction phases at the encoder side is supplemented towards the audio signal at decoder stage. Therefore, clearly the quantization phase which is modified to produce a bit stream which is scalable. This modified algorithm works well at both lower and higher bit rates. Subjective evaluations were done by audio professionals using the MUSHRA test and the mean normalized scores at various bit rates was noted and compared with the previous algorithms.

Full Text:



Sinha D and C. Sundberg, “Unequal error protection (UEP) for perceptual audio coders,” IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP), 1999, pp. 2423–2326.

Mondal, U.K, “Achieving lossless compression of audio by encoding its constituted components (LCAEC),” Innovations Syst Softw Eng Vol 15, 2019, pp.75–85.

Huang, H. Shu, and R. Yu, “Lossless Audio Compression in The New IEEE Standard for Advanced Audio Coding,” IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP), 2014, pp. 6934 – 6938.

M. Sandler and D. Black, “Scalable audio coding for compression and loss resilient streaming,” IEEE Proceeding. -Visual. Image Signal Processing., Vol. 153, No. 3, 2006, pp. 331–339.

Srivatsan Kandadai & Charles D. Creusere, “Scalable Audio Compression at Low Bitrates,” IEEE Transactions on Audio, Speech, and Language Processing. Vol.16, No.5, 2008, pp. 969- 979.

Pramila Srinivasan and Leah H. Jamieson, “High-Quality Audio Compression Using an Adaptive Wavelet Packet Decomposition and Psychoacoustic Modeling,” IEEE Transactions on Signal Processing, Vol. 46, No.4, 1998, pp.1085 – 1093.

Manas Arora,Neha Maurya, “Audio Compression in MPEG Technology,” International Journal of Scientific and Research Publications. Vol.3, No.12, 2013, pp.1-4.

D. Pan, “A tutorial on MPEG/audio compression,” IEEE Multimedia. Vol. 2, No.2, 1995, pp.60-74.

Moreno-Alvarado R.G, Mauricio Martinez-Garcia, Mariko Nakano and Héctor M. Pérez, “DCT-Compressive Sampling of Multifrequency sparse audio signals,” IEEE Latin-America Conference on Communications, 2014.

Subbarao V. Wunnava, and Craig Chin, “Multilevel Data Compression Techniques for Transmission of Audio over Networks. Proceedings,” IEEE South east Conference, 2001, pp.234 – 238.

Florin Ghido, “An Asymptotically Optimal Predictor for Stereo Lossless Audio Compression,” Proceedings of the Data Compression Conference, 2003.

Rongshan Yu and Chi Chung Ko, “Lossless Compression of Digital Audio Using Cascaded RLS-LMS Prediction.” IEEE Transactions on Audio, Speech, and Language Processing, Vol.11, No.6, 2003, pp.532 – 537.

Teddy Surya Gunawan, M. Khalif Mat Zain, Fathiah Abdul Muin and Mira Kartiwi, “Investigation of Lossless Audio Compression using IEEE 1857.2 Advanced Audio Coding,” Indonesian Journal of Electrical Engineering and Computer Science Vol.6, No.2, 2017, pp.422 – 430.

Anthony Griffin, Toni Hirvonen, Christos Tzagkarakis, Athanasios Mouchtaris and Panagiotis Tsakalides, “Single-Channel and Multi-Channel Sinusoidal Audio Coding Using Compressed Sensing,” IEEE Transactions on Audio, Speech, and Language Processing. Vol.19, No.5, 2010, pp.1382 – 1395.

Rubem J. V. de Medeiros, Edmar C. Gurj˜ao and Joˆao M. de Carvalho, “Lossy Audio Compression Via Compressed Sensing. Proceedings of the Data Compression Conference,2010.

Duarte, M. Davenport, D. Takhar, J. Laska, T. Sun, K. Kelly, and R. Baraniuk, “Single- pixel imaging via compressive sampling,” IEEE Signal Processing Magazine. Vol.25, No.2, 2008, pp.83– 91.

Larsen M.H, M. G. Christensen, and S. H. Jensen, “Variable dimension trellis-coded quantization of sinusoidal parameters,” IEEE Signal Processing Letters. Vol.15, 2008, pp.17–20.

Vafin R and W. B. Kleijn, “Entropy-constrained polar quantization and its application to audio coding,” IEEE Transactions on Audio, Speech, and Language Processing, Vol.13, No. 2, 2005, pp.220–232.

Cecchi, S.; Virgulti, M.; Primavera, A.; Piazza, F.; Bettarelli, F.; Li, J, “Investigation on audio algorithms architecture for stereo portable devices,” Journal of Audio Engineering Society, Vol.64, 2016, pp.175–188.

Creusere C, “Understanding perceptual distortion in MPEG scalable audio coding. IEEE Transactions on Audio, Speech, and Language Processing, Vol.13, No.3, 2005, pp. 422–431.


  • There are currently no refbacks.

International Journal of Electronics and Telecommunications
is a periodical of Electronics and Telecommunications Committee
of Polish Academy of Sciences

eISSN: 2300-1933