Harmonic plus noise model (HNM) divides the speech spectrum in two bands: harmonic and noise. As most of the non-periodic components are removed in harmonic part, it may be expected that HNM synthesis is less susceptible to additive noise in input speech. As HNM analysis/synthesis is performed at each glottal closure instant (GCI), errors in estimation of GCIs affect the quality of the synthesi...

This paper presents a new method for robust voiced/unvoiced segment (V/UV) classification and accurate fundamental frequency ( ) estimation in a noisy environment. For this purpose, we introduce the degree of dominance and dominance spectrum that are defined by instantaneous frequency. The degree of dominance allows us to evaluate the magnitude of individual harmonic components of speech signal...

Extracting a weak audio signal buried below a stronger one is a difficult task that may be encountered in forensic applications. Extraction of the background signal is made difficult by the signal-to-noise ratio that is clearly negative. Apart from this difficulty, the problem would look like the problem of separating different components from an audio signal. We investigate the possibility of ...

This paper presents a statistical multipich analyzer based on a source-filter model that decomposes a target music audio signal in terms of three major kinds of sound quantities: pitch (fundamental frequency: F0), timbre (spectral envelope), and intensity (amplitude). If the spectral envelope of an isolated sound is represented by an all-pole filter, linear predictive coding (LPC) can be used f...

In this paper, we propose a new scheme to analyze the spectral structure of speech signals for fundamental frequency estimation. First, we propose a pitch measure to detect the harmonic characteristics of voiced sounds on the spectrum of a speech signal. This measure utilizes the properties that there are distinct impulses located at the positions of fundamental frequency and its harmonics, and...

The efficiency and accuracy of cortical maps from optical imaging experiments have been improved using periodic stimulation protocols. The resulting data analysis requires the detection and estimation of periodic information in a multivariate dataset. To date, these analyses have relied on discrete Fourier transform (DFT) sinusoid estimates. Multitaper methods have become common statistical too...

In diffusion magnetic resonance imaging (dMRI), the diffusion signal can be reconstructed from measurements collected on single or multiple spheres in q-space using a spherical harmonic expansion. The number of measurements that can be acquired is severely limited and should be as small as possible. Previous sampling schemes have focused on using antipodal symmetry to reduce the number of sampl...

Harmonic estimation is essential for mitigating or suppressing harmonic distortions in power systems. The most important idea that spectrum analysis, waveform estimation, source classification, location, the determination of contributions, data clustering, and filter-based elimination capacity are also considered. feature extraction method a fundamental component optimization improves effective...

Abstract. In this paper we define and verify a subclass of harmonic univalent functions involving the argument of complex-value functions of the form f = h + ¯g and investigate some properties of this subclass e.g. necessary and sufficient coefficient bounds, extreme points, distortion bounds and Hadamard product.Abstract. In this paper we define and verify a subclass of harmonic univalent func...

In many signal processing applications, adaptive frequency estimation and tracking of noisy narrowband signals is often required in communications, radar, sonar, controls, biomedical signal processing, and the applications such as detection of a noisy sinusoidal signal and cancellation of periodic signals. In order to achieve the objective of frequency tracking and estimation, an adaptive finit...