The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this paper, automatic speaker verification using normal and whispered speech is explored. Typically, for speaker verification systems with varying vocal effort inputs, standard solutions such as feature mapping or addition of data during parameter estimation (training) and enrollment stages result in a trade-off between accuracy gains with whispered test data and accuracy losses (up to 70% in equal...
In this paper, we examine the descriptiveness and recognition properties of different feature representations for the analysis of musical signals, aiming in the exploration of their microand macro-structures, for the task of music genre classification. We explore nonlinear methods, such as the AM-FM model and ideas from fractal theory, so as to model the timevarying harmonic structure of musical signals...
A method widely used in speech signal analysis is based on short-time Fourier transform (STFT), but STFT only provides “average” characteristics of a signal, which can't depict the refined structure of speech. Therefore, a new speech analysis tool called fractional Fourier transform (FRFT) is introduced into this article. The transform orders for FRFT are adaptively set according to piecewise linear...
Different fingerprint recognition systems store minutiae-based fingerprint templates differently. Some store them inside a small token; some can be found in a server database. As the minutiae template is very compact, many take it for granted that the template does not contain sufficient information for reconstructing the original fingerprint. This paper proposes a scheme to reconstruct a full fingerprint...
We present a novel approach to represent transients using spectral-domain amplitude-modulated/frequency-modulated (AM-FM) functions. The model is applied to the real and imaginary parts of the Fourier transform (FT) of the transient. The suitability of the model lies in the observation that since transients are well-localized in time, the real and imaginary parts of the Fourier spectrum have a modulation...
This paper presents the parameterization of speech based on amplitude and frequency modulation (AM-FM) model and its application to speaker identification. Speech parameterization is based on three different bandwidths. The speaker identification is done using auto associative neural network. The AANN is trained with SOLO speaking style speech signal, and a network is created for each speaker. The...
The voice onset time (VOT) combines the temporal and frequency structure over very short duration. This makes the VOT detection task difficult. But the VOT is an important temporal feature. In this paper we propose a new method for the detection of VOT in speech utterances. The method uses Fourier-Bessel (FB) expansion followed by amplitude and frequency modulated (AM-FM) signal model. The FB expansion...
We introduce a novel decomposition algorithm capable of extracting locally coherent and visually meaningful texture components from images. The algorithm estimates texture dominant orientation for each coherent component and iteratively extracts it from the image based on a new quantitative coherency measure formulated in the modulation domain. The original image is perfectly reconstructed from extracted...
In this paper, a nonlinear AM-FM speech model is used to extract robust features for speaker identification. The proposed features measure the amount of amplitude and frequency modulation that the commonly used linear source-filter model and the Mel frequency cepstral coefficients (MFCC) feature fails to capture. From the short time estimates of the frequency and bandwidth, a novel set of features...
Several studies have been dedicated to the analysis and modeling of AM-FM modulations in speech and different algorithms have been proposed for the exploitation of modulations in speech applications. This paper details a statistical analysis of amplitude modulations using a multiband AM-FM analysis framework. The aim of this study is to analyze the phonetic- and speaker-dependency of modulations in...
This paper describes classification of gait patterns from a waist-mounted triaxial accelerometer. A feature extraction technique using empirical mode decomposition (EMD) and an amplitude/frequency modulation (AM-FM) model is proposed for the classification of walking activities from accelerometry data. A set of novel features, including AM, instantaneous frequency (IF) and instantaneous amplitude...
For medical and epidemiologic investigators and caregivers, one powerful functionality yet to be developed is the ability to group retinal images based upon common pathologic appearance. Such a tool would enable advances in evidence-based medicine and would accelerate automated or computer-assisted screening and diagnosis. In this report, we show that current, traditional content based image retrieval...
We present new multidimensional amplitude-modulation frequency-modulation (AM-FM) methods for motion estimation. For a single AM-FM component we show that the optical flow constraint leads to separate equations for amplitude modulation (AM) and frequency modulation (FM). We compare our approach with phase-based estimation developed by Fleet and Jepson and also the original optical flow method by Horn...
In this paper, a new technique based on the Fourier-Bessel (FB) expansion is presented for separating multiple formants of a speech signal. The discrete energy separation algorithm (DESA) is applied to an isolated speech formant to extract the instantaneous frequency (IF) and the time-varying amplitude envelope (AE) of the formant. It is demonstrated that the proposed technique which is called the...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.