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

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dc.citedby1
dc.contributor.authorNagi J.en_US
dc.contributor.authorYap K.S.en_US
dc.contributor.authorTiong S.K.en_US
dc.contributor.authorAhmed S.K.en_US
dc.contributor.authorNagi F.en_US
dc.contributor.authorid25825455100en_US
dc.contributor.authorid24448864400en_US
dc.contributor.authorid15128307800en_US
dc.contributor.authorid25926812900en_US
dc.contributor.authorid56272534200en_US
dc.date.accessioned2023-12-29T07:54:39Z
dc.date.available2023-12-29T07:54:39Z
dc.date.issued2008
dc.description.abstractEfficient 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.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo4631887
dc.identifier.doi10.1109/ITSIM.2008.4631887
dc.identifier.scopus2-s2.0-57349187722
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-57349187722&doi=10.1109%2fITSIM.2008.4631887&partnerID=40&md5=f090a19e80603f112791e54c0b04ccfe
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/30851
dc.identifier.volume3
dc.sourceScopus
dc.sourcetitleProceedings - International Symposium on Information Technology 2008, ITSim
dc.subjectArtificial intelligence
dc.subjectBandpass filters
dc.subjectCivil aviation
dc.subjectDiscrete Fourier transforms
dc.subjectFourier transforms
dc.subjectImage retrieval
dc.subjectImpulse response
dc.subjectInformation technology
dc.subjectPower spectrum
dc.subjectSignal processing
dc.subjectSpectrum analysis
dc.subjectSpectrum analyzers
dc.subjectSupport vector machines
dc.subjectTelecommunication
dc.subjectTelecommunication equipment
dc.subjectVectors
dc.subjectCarrier frequencies
dc.subjectDecision logics
dc.subjectDetection models
dc.subjectDetection schemes
dc.subjectDetection techniques
dc.subjectDtmf frequencies
dc.subjectEfficient methods
dc.subjectFinite impulse responses
dc.subjectFrequency variations
dc.subjectHybrid signal processing
dc.subjectInput samples
dc.subjectIntelligent classifications
dc.subjectIntelligent detections
dc.subjectMulti frequencies
dc.subjectPower Spectrum analysis
dc.subjectSupport vectors
dc.subjectWhite gaussian noises
dc.subjectFrequency response
dc.titleIntelligent detection of DTMF tones using a hybrid signal processing technique with support vector machinesen_US
dc.typeConference paperen_US
dspace.entity.typePublication
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