This article introduces the second generation of the Discrete Shapelet Transform (DST-II), a tool... more This article introduces the second generation of the Discrete Shapelet Transform (DST-II), a tool created for fusing three types of information: time, frequency and shape-related. Considered a particular Discrete Wavelet Transform (DWT), it allows a productive time-frequency-shape (TFS) joint analysis. In the proposed approach, both the procedure to attain the corresponding filters coefficients and the interpretation of the transformed signal are simplified in relation to the usage of its predecessor, i.e., the DST. Throughout the article, the DST-II formulation is described in detail, including a numerical example, a prototype for use in a diversity of fields and an application on spike and overlap sorting, reassuring the efficacy of the new transform.
This paper presents a method to enhance microcalcifications and classify their borders by applyin... more This paper presents a method to enhance microcalcifications and classify their borders by applying the wavelet transform. Decomposing an image and removing its low frequency sub-band the microcalcifications are enhanced. Analyzing the effects of perturbations on high frequency sub-band itpsilas possible to classify its borders as smooth, rugged or undefined. Results show a false positive reduction of 69.27% using a region growing algorithm.
In this paper, the relationship between the filter coefficients and the scaling and wavelet funct... more In this paper, the relationship between the filter coefficients and the scaling and wavelet functions of the Discrete Wavelet Transform is presented and exemplified from a practical point-of-view. The explanations complement the wavelet theory, that is well documented in the literature, being important for researchers who work with this tool for time-frequency analysis.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011
Parkinson's disease (PD) automatic identification has been actively pursued over several work... more Parkinson's disease (PD) automatic identification has been actively pursued over several works in the literature. In this paper, we deal with this problem by applying evolutionary-based techniques in order to find the subset of features that maximize the accuracy of the Optimum-Path Forest (OPF) classifier. The reason for the choice of this classifier relies on its fast training phase, given
2006 Proceeding of the Thrity-Eighth Southeastern Symposium on System Theory, 2006
Page 1. A wavelet-PCA approach for content-based image retrieval Marcelo Franceschi de Bianchi, R... more Page 1. A wavelet-PCA approach for content-based image retrieval Marcelo Franceschi de Bianchi, Rodrigo Capobianco Guido, André Luiz Nogueira, Paula Padovan Centro Universitário do Norte Paulista Rua Ipiranga 3460 ...
This paper presents a method to study the distribution of the articulatory information on time-fr... more This paper presents a method to study the distribution of the articulatory information on time-frequency representation calculated from the acoustic speech signal, whose parametrization is achieved using the wavelet packet transform. The main focus is on measuring the relevant acoustic information, in terms of statistical association, for the inference of critical articulator positions. The rank correlation Kendall coefficient is used as the relevance measure. The maps of relevant time-frequency features are calculated for the MOCHA-TIMIT database, where the articulatory information is represented by trajectories of specific positions in the vocal tract. Relevant maps are estimated on specific phones, for which a given articulator is known to be critical. The usefulness of the relevant maps is tested in an acoustic-to-articulatory mapping system based on gaussian mixture models.
Seventh IEEE International Symposium on Multimedia (ISM'05), 2005
... Discrete Wavelet Transform and Support Vector Machine Applied to Pathological Voice SignalsId... more ... Discrete Wavelet Transform and Support Vector Machine Applied to Pathological Voice SignalsIdentification A ... using a wide-band microphone and professional software, sampling the voices at 22050 Hz, 16 ... Each speaker was asked to sustain the sound for nearly 5 seconds, in ...
This work describes a novel algorithm to identify laryngeal pathologies, by the digital analysis ... more This work describes a novel algorithm to identify laryngeal pathologies, by the digital analysis of the voice. It is based on Daubechies' discrete wavelet transform (DWT-db), linear prediction coefficients (LPC), and least squares support vector machines (LS-SVM). Wavelets with different support-sizes and three LS-SVM kernels are compared. Particularly, the proposed approach, implemented with modest computer requirements, leads to an adequate larynx pathology classifier to identify nodules in vocal folds. It presents over 90% of classification accuracy and has a low order of computational complexity in relation to the speech signal's length. ᭧
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2011
Parkinson's disease (PD) automatic identification has been actively pursued over several work... more Parkinson's disease (PD) automatic identification has been actively pursued over several works in the literature. In this paper, we deal with this problem by applying evolutionary-based techniques in order to find the subset of features that maximize the accuracy of the Optimum-Path Forest (OPF) classifier. The reason for the choice of this classifier relies on its fast training phase, given that each possible solution to be optimized is guided by the OPF accuracy. We also show results that improved other ones recently obtained in the context of PD automatic identification.
Seventh IEEE International Symposium on Multimedia (ISM'05), 2005
This paper describes a novel technique for audio coding, a lossy compression algorithm, that cons... more This paper describes a novel technique for audio coding, a lossy compression algorithm, that considers perceptual and rate-distortion criteria. It is based on matched finite impulse response (FIR) wavelet-packet-like filter banks, the filter coefficients being produced adaptively according to the input signal. This technique achieves perceptually transparent coding of high-quality audio, signals sampled at 44.1 KHz-16 bits PCM, at bit rates of about 54-64 Kbps. The matched filter-bank makes a time-frequencyshape analysis, reducing the number of sub-bands requiring quantization. The decoder that implements this algorithm works effectively in real time. This reassures the efficacy of our technique.
Proceedings of the Thirty-Seventh Southeastern Symposium on System Theory, 2005. SSST '05., 2005
TRYING DIFFERENT WAVELETS ON THE SEARCH FOR VOICE DISORDERS SORTING ... Rodrigo C. Guido&... more TRYING DIFFERENT WAVELETS ON THE SEARCH FOR VOICE DISORDERS SORTING ... Rodrigo C. Guido' Jos& C. Pereimi Everrhon Fonsecat ... School of Engineering from University of SZo Paul0 at SBo Carlos - Department of Electrical Engineering. AV. do Trabalhador ...
2006 Proceeding of the Thrity-Eighth Southeastern Symposium on System Theory, 2006
Page 1. Support Vector Machines and Wavelets for Voice Disorder Sorting. Rodrigo Capobianco Guido... more Page 1. Support Vector Machines and Wavelets for Voice Disorder Sorting. Rodrigo Capobianco Guido , José Carlos Pereira, Everthon Silva Fonseca, Carlos Dias Maciel, Lucimar Sasso Vieira, Fabrıcio Lopes Sanchez Márcio Borges A. Guilerme, and Sılvio Barbon Jr. ...
ABSTRACT In this letter, we present different approaches for music genre classification. The prop... more ABSTRACT In this letter, we present different approaches for music genre classification. The proposed techniques, which are composed of a feature extraction stage followed by a classification procedure, explore both the variations of parameters used as input and the classifier architecture. Tests were carried out with three styles of music, namely blues, classical, and lounge, which are considered informally by some musicians as being “big dividers” among music genres, showing the efficacy of the proposed algorithms and establishing a relationship between the relevance of each set of parameters for each music style and each classifier. In contrast to other works, entropies and fractal dimensions are the features adopted for the classifications.
Journal of Computational and Applied Mathematics, 2009
Dynamic Time Warping (DTW), a pattern matching technique traditionally used for restricted vocabu... more Dynamic Time Warping (DTW), a pattern matching technique traditionally used for restricted vocabulary speech recognition, is based on a temporal alignment of the input signal with the template models. The principal drawback of DTW is its high computational cost as the lengths of the signals increase. This paper shows extended results over our previously published conference paper, which introduces an
This paper proposes an improved voice activity detection (VAD) algorithm using wavelet and suppor... more This paper proposes an improved voice activity detection (VAD) algorithm using wavelet and support vector machine (SVM) for European Telecommunication Standards Institution (ETSI) adaptive multi-rate (AMR) narrow-band (NB) and wide-band (WB) speech codecs. First, based on the wavelet transform, the original IIR filter bank and pitch/tone detector are implemented, respectively, via the wavelet filter bank and the wavelet-based pitch/tone detection
2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence), 2008
Abstract This paper presents a method to enhance microcalcifications and classify their borders b... more Abstract This paper presents a method to enhance microcalcifications and classify their borders by applying the wavelet transform. Decomposing an image and removing its low frequency sub-band the microcalcifications are enhanced. Analyzing the effects of ...
2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011
Abstract In this paper we deal with the problem of feature selection by introducing a new approac... more Abstract In this paper we deal with the problem of feature selection by introducing a new approach based on Gravitational Search Algorithm (GSA). The proposed algorithm combines the optimization behavior of GSA together with the speed of Optimum-Path Forest (OPF) classifier in order to provide a fast and accurate framework for feature selection. Experiments on datasets obtained from a wide range of applications, such as vowel recognition, image classification and fraud detection in power distribution systems are ...
This article introduces the second generation of the Discrete Shapelet Transform (DST-II), a tool... more This article introduces the second generation of the Discrete Shapelet Transform (DST-II), a tool created for fusing three types of information: time, frequency and shape-related. Considered a particular Discrete Wavelet Transform (DWT), it allows a productive time-frequency-shape (TFS) joint analysis. In the proposed approach, both the procedure to attain the corresponding filters coefficients and the interpretation of the transformed signal are simplified in relation to the usage of its predecessor, i.e., the DST. Throughout the article, the DST-II formulation is described in detail, including a numerical example, a prototype for use in a diversity of fields and an application on spike and overlap sorting, reassuring the efficacy of the new transform.
This paper presents a method to enhance microcalcifications and classify their borders by applyin... more This paper presents a method to enhance microcalcifications and classify their borders by applying the wavelet transform. Decomposing an image and removing its low frequency sub-band the microcalcifications are enhanced. Analyzing the effects of perturbations on high frequency sub-band itpsilas possible to classify its borders as smooth, rugged or undefined. Results show a false positive reduction of 69.27% using a region growing algorithm.
In this paper, the relationship between the filter coefficients and the scaling and wavelet funct... more In this paper, the relationship between the filter coefficients and the scaling and wavelet functions of the Discrete Wavelet Transform is presented and exemplified from a practical point-of-view. The explanations complement the wavelet theory, that is well documented in the literature, being important for researchers who work with this tool for time-frequency analysis.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011
Parkinson's disease (PD) automatic identification has been actively pursued over several work... more Parkinson's disease (PD) automatic identification has been actively pursued over several works in the literature. In this paper, we deal with this problem by applying evolutionary-based techniques in order to find the subset of features that maximize the accuracy of the Optimum-Path Forest (OPF) classifier. The reason for the choice of this classifier relies on its fast training phase, given
2006 Proceeding of the Thrity-Eighth Southeastern Symposium on System Theory, 2006
Page 1. A wavelet-PCA approach for content-based image retrieval Marcelo Franceschi de Bianchi, R... more Page 1. A wavelet-PCA approach for content-based image retrieval Marcelo Franceschi de Bianchi, Rodrigo Capobianco Guido, André Luiz Nogueira, Paula Padovan Centro Universitário do Norte Paulista Rua Ipiranga 3460 ...
This paper presents a method to study the distribution of the articulatory information on time-fr... more This paper presents a method to study the distribution of the articulatory information on time-frequency representation calculated from the acoustic speech signal, whose parametrization is achieved using the wavelet packet transform. The main focus is on measuring the relevant acoustic information, in terms of statistical association, for the inference of critical articulator positions. The rank correlation Kendall coefficient is used as the relevance measure. The maps of relevant time-frequency features are calculated for the MOCHA-TIMIT database, where the articulatory information is represented by trajectories of specific positions in the vocal tract. Relevant maps are estimated on specific phones, for which a given articulator is known to be critical. The usefulness of the relevant maps is tested in an acoustic-to-articulatory mapping system based on gaussian mixture models.
Seventh IEEE International Symposium on Multimedia (ISM'05), 2005
... Discrete Wavelet Transform and Support Vector Machine Applied to Pathological Voice SignalsId... more ... Discrete Wavelet Transform and Support Vector Machine Applied to Pathological Voice SignalsIdentification A ... using a wide-band microphone and professional software, sampling the voices at 22050 Hz, 16 ... Each speaker was asked to sustain the sound for nearly 5 seconds, in ...
This work describes a novel algorithm to identify laryngeal pathologies, by the digital analysis ... more This work describes a novel algorithm to identify laryngeal pathologies, by the digital analysis of the voice. It is based on Daubechies' discrete wavelet transform (DWT-db), linear prediction coefficients (LPC), and least squares support vector machines (LS-SVM). Wavelets with different support-sizes and three LS-SVM kernels are compared. Particularly, the proposed approach, implemented with modest computer requirements, leads to an adequate larynx pathology classifier to identify nodules in vocal folds. It presents over 90% of classification accuracy and has a low order of computational complexity in relation to the speech signal's length. ᭧
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2011
Parkinson's disease (PD) automatic identification has been actively pursued over several work... more Parkinson's disease (PD) automatic identification has been actively pursued over several works in the literature. In this paper, we deal with this problem by applying evolutionary-based techniques in order to find the subset of features that maximize the accuracy of the Optimum-Path Forest (OPF) classifier. The reason for the choice of this classifier relies on its fast training phase, given that each possible solution to be optimized is guided by the OPF accuracy. We also show results that improved other ones recently obtained in the context of PD automatic identification.
Seventh IEEE International Symposium on Multimedia (ISM'05), 2005
This paper describes a novel technique for audio coding, a lossy compression algorithm, that cons... more This paper describes a novel technique for audio coding, a lossy compression algorithm, that considers perceptual and rate-distortion criteria. It is based on matched finite impulse response (FIR) wavelet-packet-like filter banks, the filter coefficients being produced adaptively according to the input signal. This technique achieves perceptually transparent coding of high-quality audio, signals sampled at 44.1 KHz-16 bits PCM, at bit rates of about 54-64 Kbps. The matched filter-bank makes a time-frequencyshape analysis, reducing the number of sub-bands requiring quantization. The decoder that implements this algorithm works effectively in real time. This reassures the efficacy of our technique.
Proceedings of the Thirty-Seventh Southeastern Symposium on System Theory, 2005. SSST '05., 2005
TRYING DIFFERENT WAVELETS ON THE SEARCH FOR VOICE DISORDERS SORTING ... Rodrigo C. Guido&... more TRYING DIFFERENT WAVELETS ON THE SEARCH FOR VOICE DISORDERS SORTING ... Rodrigo C. Guido' Jos& C. Pereimi Everrhon Fonsecat ... School of Engineering from University of SZo Paul0 at SBo Carlos - Department of Electrical Engineering. AV. do Trabalhador ...
2006 Proceeding of the Thrity-Eighth Southeastern Symposium on System Theory, 2006
Page 1. Support Vector Machines and Wavelets for Voice Disorder Sorting. Rodrigo Capobianco Guido... more Page 1. Support Vector Machines and Wavelets for Voice Disorder Sorting. Rodrigo Capobianco Guido , José Carlos Pereira, Everthon Silva Fonseca, Carlos Dias Maciel, Lucimar Sasso Vieira, Fabrıcio Lopes Sanchez Márcio Borges A. Guilerme, and Sılvio Barbon Jr. ...
ABSTRACT In this letter, we present different approaches for music genre classification. The prop... more ABSTRACT In this letter, we present different approaches for music genre classification. The proposed techniques, which are composed of a feature extraction stage followed by a classification procedure, explore both the variations of parameters used as input and the classifier architecture. Tests were carried out with three styles of music, namely blues, classical, and lounge, which are considered informally by some musicians as being “big dividers” among music genres, showing the efficacy of the proposed algorithms and establishing a relationship between the relevance of each set of parameters for each music style and each classifier. In contrast to other works, entropies and fractal dimensions are the features adopted for the classifications.
Journal of Computational and Applied Mathematics, 2009
Dynamic Time Warping (DTW), a pattern matching technique traditionally used for restricted vocabu... more Dynamic Time Warping (DTW), a pattern matching technique traditionally used for restricted vocabulary speech recognition, is based on a temporal alignment of the input signal with the template models. The principal drawback of DTW is its high computational cost as the lengths of the signals increase. This paper shows extended results over our previously published conference paper, which introduces an
This paper proposes an improved voice activity detection (VAD) algorithm using wavelet and suppor... more This paper proposes an improved voice activity detection (VAD) algorithm using wavelet and support vector machine (SVM) for European Telecommunication Standards Institution (ETSI) adaptive multi-rate (AMR) narrow-band (NB) and wide-band (WB) speech codecs. First, based on the wavelet transform, the original IIR filter bank and pitch/tone detector are implemented, respectively, via the wavelet filter bank and the wavelet-based pitch/tone detection
2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence), 2008
Abstract This paper presents a method to enhance microcalcifications and classify their borders b... more Abstract This paper presents a method to enhance microcalcifications and classify their borders by applying the wavelet transform. Decomposing an image and removing its low frequency sub-band the microcalcifications are enhanced. Analyzing the effects of ...
2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011
Abstract In this paper we deal with the problem of feature selection by introducing a new approac... more Abstract In this paper we deal with the problem of feature selection by introducing a new approach based on Gravitational Search Algorithm (GSA). The proposed algorithm combines the optimization behavior of GSA together with the speed of Optimum-Path Forest (OPF) classifier in order to provide a fast and accurate framework for feature selection. Experiments on datasets obtained from a wide range of applications, such as vowel recognition, image classification and fraud detection in power distribution systems are ...
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