Intelligent detection of DTMF tones using a hybrid signal processing technique with support vector machines

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Efficient methods for DTMF signal detection are important for developing telecommunication equipment. This paper presents a hybrid signal processing and artificial intelligence based approach for the detection of Dual-tone Multifrequency (DTMF) tones under the influence of White Gaussian Noise (WGN) and frequency variation. Key innovations include the use of a Finite Impulse Response (FIR) bandpass filter for reduction of noise from DTMF input samples, and Support Vector Machines (SVM) for intelligent classification of the detected DTMF carrier frequencies. The proposed hybrid DTMF detector scheme is based on power spectrum analysis by means of the Discrete Fourier Transform (DFT). The Goertzel's Algorithm is used to estimate the seven fundamental DTMF carrier frequencies. The tone detection scheme employs decision logic to detect valid DTMF tones from low and high DTMF frequency groups. Comparison of this hybrid DTMF tone detection model with existing DTMF detection techniques proves the merits of this proposed scheme.

Original languageEnglish
Title of host publicationProceedings - International Symposium on Information Technology 2008, ITSim
DOIs
Publication statusPublished - 12 Dec 2008
EventInternational Symposium on Information Technology 2008, ITSim - Kuala Lumpur, Malaysia
Duration: 26 Aug 200829 Aug 2008

Publication series

NameProceedings - International Symposium on Information Technology 2008, ITSim
Volume3

Other

OtherInternational Symposium on Information Technology 2008, ITSim
CountryMalaysia
CityKuala Lumpur
Period26/08/0829/08/08

Fingerprint

Telecommunication equipment
Signal detection
FIR filters
Power spectrum
Bandpass filters
Discrete Fourier transforms
Spectrum analysis
Artificial intelligence
Support vector machines
Signal processing
Innovation
Detectors

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Information Systems
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Nagi, J., Yap, K. S., Tiong, S. K., Khaleel Ahmed, S., & Nagi, F. (2008). Intelligent detection of DTMF tones using a hybrid signal processing technique with support vector machines. In Proceedings - International Symposium on Information Technology 2008, ITSim [4631887] (Proceedings - International Symposium on Information Technology 2008, ITSim; Vol. 3). https://doi.org/10.1109/ITSIM.2008.4631887
Nagi, J. ; Yap, Keem Siah ; Tiong, Sieh Kiong ; Khaleel Ahmed, Syed ; Nagi, F. / Intelligent detection of DTMF tones using a hybrid signal processing technique with support vector machines. Proceedings - International Symposium on Information Technology 2008, ITSim. 2008. (Proceedings - International Symposium on Information Technology 2008, ITSim).
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Nagi, J, Yap, KS, Tiong, SK, Khaleel Ahmed, S & Nagi, F 2008, Intelligent detection of DTMF tones using a hybrid signal processing technique with support vector machines. in Proceedings - International Symposium on Information Technology 2008, ITSim., 4631887, Proceedings - International Symposium on Information Technology 2008, ITSim, vol. 3, International Symposium on Information Technology 2008, ITSim, Kuala Lumpur, Malaysia, 26/08/08. https://doi.org/10.1109/ITSIM.2008.4631887

Intelligent detection of DTMF tones using a hybrid signal processing technique with support vector machines. / Nagi, J.; Yap, Keem Siah; Tiong, Sieh Kiong; Khaleel Ahmed, Syed; Nagi, F.

Proceedings - International Symposium on Information Technology 2008, ITSim. 2008. 4631887 (Proceedings - International Symposium on Information Technology 2008, ITSim; Vol. 3).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - Efficient methods for DTMF signal detection are important for developing telecommunication equipment. This paper presents a hybrid signal processing and artificial intelligence based approach for the detection of Dual-tone Multifrequency (DTMF) tones under the influence of White Gaussian Noise (WGN) and frequency variation. Key innovations include the use of a Finite Impulse Response (FIR) bandpass filter for reduction of noise from DTMF input samples, and Support Vector Machines (SVM) for intelligent classification of the detected DTMF carrier frequencies. The proposed hybrid DTMF detector scheme is based on power spectrum analysis by means of the Discrete Fourier Transform (DFT). The Goertzel's Algorithm is used to estimate the seven fundamental DTMF carrier frequencies. The tone detection scheme employs decision logic to detect valid DTMF tones from low and high DTMF frequency groups. Comparison of this hybrid DTMF tone detection model with existing DTMF detection techniques proves the merits of this proposed scheme.

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Nagi J, Yap KS, Tiong SK, Khaleel Ahmed S, Nagi F. Intelligent detection of DTMF tones using a hybrid signal processing technique with support vector machines. In Proceedings - International Symposium on Information Technology 2008, ITSim. 2008. 4631887. (Proceedings - International Symposium on Information Technology 2008, ITSim). https://doi.org/10.1109/ITSIM.2008.4631887