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

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)...

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Main Authors:	Nagi J., Yap K.S., Tiong S.K., Ahmed S.K., Nagi F.
Other Authors:	25825455100
Format:	Conference paper
Published:	2023
Subjects:	Artificial intelligence Bandpass filters Civil aviation Discrete Fourier transforms Fourier transforms Image retrieval Impulse response Information technology Power spectrum Signal processing Spectrum analysis Spectrum analyzers Support vector machines Telecommunication Telecommunication equipment Vectors Carrier frequencies Decision logics Detection models Detection schemes Detection techniques Dtmf frequencies Efficient methods Finite impulse responses Frequency variations Hybrid signal processing Input samples Intelligent classifications Intelligent detections Multi frequencies Power Spectrum analysis Support vectors White gaussian noises Frequency response
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id	my.uniten.dspace-30851
record_format	dspace
spelling	my.uniten.dspace-308512023-12-29T15:54:39Z Intelligent detection of DTMF tones using a hybrid signal processing technique with support vector machines Nagi J. Yap K.S. Tiong S.K. Ahmed S.K. Nagi F. 25825455100 24448864400 15128307800 25926812900 56272534200 Artificial intelligence Bandpass filters Civil aviation Discrete Fourier transforms Fourier transforms Image retrieval Impulse response Information technology Power spectrum Signal processing Spectrum analysis Spectrum analyzers Support vector machines Telecommunication Telecommunication equipment Vectors Carrier frequencies Decision logics Detection models Detection schemes Detection techniques Dtmf frequencies Efficient methods Finite impulse responses Frequency variations Hybrid signal processing Input samples Intelligent classifications Intelligent detections Multi frequencies Power Spectrum analysis Support vectors White gaussian noises Frequency response 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. � 2008 IEEE. Final 2023-12-29T07:54:39Z 2023-12-29T07:54:39Z 2008 Conference paper 10.1109/ITSIM.2008.4631887 2-s2.0-57349187722 https://www.scopus.com/inward/record.uri?eid=2-s2.0-57349187722&doi=10.1109%2fITSIM.2008.4631887&partnerID=40&md5=f090a19e80603f112791e54c0b04ccfe https://irepository.uniten.edu.my/handle/123456789/30851 3 4631887 Scopus
institution	Universiti Tenaga Nasional
building	UNITEN Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Tenaga Nasional
content_source	UNITEN Institutional Repository
url_provider	http://dspace.uniten.edu.my/
topic	Artificial intelligence Bandpass filters Civil aviation Discrete Fourier transforms Fourier transforms Image retrieval Impulse response Information technology Power spectrum Signal processing Spectrum analysis Spectrum analyzers Support vector machines Telecommunication Telecommunication equipment Vectors Carrier frequencies Decision logics Detection models Detection schemes Detection techniques Dtmf frequencies Efficient methods Finite impulse responses Frequency variations Hybrid signal processing Input samples Intelligent classifications Intelligent detections Multi frequencies Power Spectrum analysis Support vectors White gaussian noises Frequency response
spellingShingle	Artificial intelligence Bandpass filters Civil aviation Discrete Fourier transforms Fourier transforms Image retrieval Impulse response Information technology Power spectrum Signal processing Spectrum analysis Spectrum analyzers Support vector machines Telecommunication Telecommunication equipment Vectors Carrier frequencies Decision logics Detection models Detection schemes Detection techniques Dtmf frequencies Efficient methods Finite impulse responses Frequency variations Hybrid signal processing Input samples Intelligent classifications Intelligent detections Multi frequencies Power Spectrum analysis Support vectors White gaussian noises Frequency response Nagi J. Yap K.S. Tiong S.K. Ahmed S.K. Nagi F. Intelligent detection of DTMF tones using a hybrid signal processing technique with support vector machines
description	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. � 2008 IEEE.
author2	25825455100
author_facet	25825455100 Nagi J. Yap K.S. Tiong S.K. Ahmed S.K. Nagi F.
format	Conference paper
author	Nagi J. Yap K.S. Tiong S.K. Ahmed S.K. Nagi F.
author_sort	Nagi J.
title	Intelligent detection of DTMF tones using a hybrid signal processing technique with support vector machines
title_short	Intelligent detection of DTMF tones using a hybrid signal processing technique with support vector machines
title_full	Intelligent detection of DTMF tones using a hybrid signal processing technique with support vector machines
title_fullStr	Intelligent detection of DTMF tones using a hybrid signal processing technique with support vector machines
title_full_unstemmed	Intelligent detection of DTMF tones using a hybrid signal processing technique with support vector machines
title_sort	intelligent detection of dtmf tones using a hybrid signal processing technique with support vector machines
publishDate	2023
_version_	1806424528369221632
score	13.222552

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

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