Low Bit-Rate Parametric Coding

Authors

  • Djadjat Sudaradjat Universitas Bina Sarana Informatika
  • Andi Rosano Universitas Bina Sarana Informatika

DOI:

https://doi.org/10.31294/paradigma.v24i2.1391

Keywords:

LPC, Speech Processing, Speech Compression

Abstract

With a low bit rate will be obtained savings in the use of bandwidth transmission channels and memory. In coding the human voice signal, an artificial voice-producing model is made to obtain a low bit rate, which is known as the parametric coding method. With the parametric coding method, the human voice signal can produce a lower bit rate than the waveform coding method. For example, the waveform coding method will be limited by a minimum sampling frequency which according to the Shannon-Nyquist theorem states that so that no information is lost when sampling the signal, the sampling speed must be at least twice the bandwidth of the signal. Thus, the lowest bit rate waveform encoding that can be achieved is by the Delta Modulation system which is 8 Kbit/sec. While the signal parametric coding can achieve a lower bit rate of 2.4 Kbit/sec by the LPC (Linear Predictive Coding) system.

References

Adam J. Chong, 1. M. (2020). Effects of consonantal constrictions on voice quality. The Journal of the Acoustical Society of America 148, EL65 (2020); doi: 10.1121/10.0001585, 65-71.

Djadjat Sudaradjat, S. A. (2020). Aplikasi Pengolahan Sinyal Suara pada Teknologi Kecerdasan Buatan. INSANtek – Jurnal Inovasi dan Sains Teknik Elektro, 88-95.

Gibson, J. (2019). Mutual Information, the Linear Prediction Model, and CELP Voice Codecs. Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 16 April 2019 doi:10.20944/preprints201904.0184.v1, 1-14.

Gibson, J. D. (2016). Speech Compression. Department of Electrical and Computer Engineering, University of California, Santa Barbara, CA 93118, USA;: Information 2016, 7, 32; doi:10.3390/info7020032.

Hamid, O. K. (2017). Speech Sound Coding Using Linear Predictive . Journal of Information, Communication, and Intelligence Sistems (JICIS) Volume 3, Issue 1, May 2017, 13-17.

Hernando Castaneda Mari, M. J. (2018). Theory , Algorithms , Implementation and Practice of Power Density Signal by Autocorrelation Modeling. https://www.researchgate.net/publication/325019198, 1-20.

Jurafsky. (2018). Speech and Language Processing. Third Edition Draft.

Kala, A. &. (2015). Speech Analysis and Synthesis using Vocoder. International Journal For Trends In Engineering & Technology.

Lee, L.-M. (2014). Model adaptation method for recognition of speech with missing frames. The Journal of the Acoustical Society of America 135, EL166 (2014); doi: 10.1121/1.4865264, 166-171.

Modi, D. (2015). Speech Cpmpression using LPC. Adaptive Signal Processing Term Paper, 1-4.

Mr. Mohit Narayanbhai Raja*, M. P. (2015). LINEAR PREDICTIVE CODING. INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH , 373-379.

Niesler*†, L. L. (2019). Feature trajectory dynamic time warping for clustering of speech segments. EURASIP Journal on Audio, Speech, and Music, 1-9.

Ning*, K. (2017). Compressed Sensing Speech Signal Enhancement Research. Indonesia: Indonesian Journal of Electrical Engineering and Computer Science, Vol. 6, No. 1, April 2017, pp. 26 ~ 35, DOI: 10.11591/ijeecs.v6.i1.pp26-35 .

Sanjaya, W. M. (2018). Speech Recognition using Linear Predictive Coding (LPC) and Adaptive Neuro-Fuzzy (ANFIS) to Control 5 DoF Arm Robot. IOP Conf. Series: Journal of Physics: Conf. Series 1090 (2018) 012046 doi :10.1088/1742-6596/1090/1/012046, 1-10.

Singh, N. (2015). Digital Signal Processing for Speech Signals. Bilingual International Conference on Information Technology: Yesterday, Toady, and Tomorrow, 19-21 Feburary 2015, pp. 134-138, 134-138.

Sudaradjat, D. (1993). Pemrosesan Sinyal Suara Dengan Metode LPC. Bandung: Institut Teknologi Bandung.

Sudaradjat, D. (2019). Teknik Adaptive Pada Modulasi Delta. Paradigma, Volume XXI No. 2 September 2019, http://ejournal.bsi.ac.id/ejurnal/index.php/paradigma, 137-142.

Uday Mithapelli, S. P. (2014). Implementation of Speech Compression Using Linear Predictive Coding (LPC) with Tms320c6713dsk and Comparison with Other Platforms. International Journal of Emerging Engineering Research and Technology Volume 2, Issue 2, May 2014, PP 91-95, 91-95.

Downloads

Published

2022-09-02

How to Cite

Sudaradjat, D., & Rosano, A. (2022). Low Bit-Rate Parametric Coding. Paradigma - Jurnal Komputer Dan Informatika, 24(2), 125-129. https://doi.org/10.31294/paradigma.v24i2.1391