نتایج جستجو برای: musical noise

تعداد نتایج: 214891  

2008
Rory A. Lewis Amanda Cohen Wenxin Jiang Zbigniew W. Ras

In the continuing investigation of identifying musical instruments in a polyphonic domain, we present a system that can identify an instrument in a polyphonic domain with added noise of numerous interacting and conflicting instruments in an orchestra. A hierarchical tree specifically designed for the breakdown of polyphonic sounds is used to enhance training of classifiers to correctly estimate...

1997
Stefan Oberle

An extension of the HMM-based speech enhancement approach [1] is presented. The HMM-based scheme uses hidden Markov models (HMM) to control a state-dependent Wiener filter, which is used to process the noisy speech signal. This scheme gives enhanced speech signals without the annoying tonal artefacts (‘musical noise’) of the spectral subtraction approach. However, parts of the enhanced signal o...

2003
Michael T. Johnson Andrew C. Lindgren Richard J. Povinelli Xiaolong Yuan

This paper presents the implementation of two nonlinear noise reduction methods applied to speech enhancement. The methods are based on embedding the noisy signal in a high-dimensional reconstructed phase space and applying singular value decomposition to project the signal into a lower dimension. The advantages of these nonlinear methods include that they do not require explicit models of nois...

2000
Anssi Klapuri Tuomas Virtanen Jan-Markus Holm

A method for the estimation of the multiple pitches of concurrent musical sounds is described. Experimental data comprised sung vowels and the whole pitch range of 26 musical instruments. Multipitch estimation was performed at the level of a single time frame for random pitch and sound source combinations. Note error rates for mixtures ranging from one to six simultaneous sounds were 2.1 %, 2.4...

2007
César Alonso Abad

In this thesis a novel multiresolution approach for note detection in a polyphonic mix is proposed. The idea is to use a set of wavelets whose lengths are adapted to the theoretical fundamental period of musical notes. Using the typical wavelet dyadic decomposition we can generate a set of wavelets that match the fundamental frequency (F0) of a given note in every octave. Therefore, using a set...

The concept of Iranian traditional musical modes, namely DASTGÄH, is the basis for the traditional music system. The concept introduces seven DASTGÄHs. It is not an easy process to distinguish these modes and such practice is commonly performed by an experienced person in this field. Apparently, applying artificial intelligence to do such classification requires a combination of the basic infor...

In the current research brain effective networks related to happy and sad emotions are studied during listening to music. Connectivity patterns among different EEG channels were extracted using multivariate autoregressive modeling and partial directed coherence while participants listened to musical excerpts. Both classical and Iranian musical selections were used as stimulus. Participants’ se...

2011
Ch.V.Rama Rao Jayaprakash Narayan

The noise signal does not affect uniformly the speech signal over the whole spectrum isn the case of colored noise. In order to deal with speech improvement in such situations a new spectral subtraction algorithm is proposed for reducing colored noise from noise corrupted speech. The spectrum is divided into frequency sub-bands based on a nonlinear multiband bark scale. For each sub-band, the n...

Journal: :پژوهشنامه نقد ادبی و بلاغت 0
جمیله اخیانی استادیار زبان و ادبیات فارسی دانشگاه زنجان اصغر بیرانوند دانش آموخته کارشناسی ارشد زبان و ادبیات فارسی دانشگاه زنجان

one of the subjects that researchers are agreed on is hafez acquaintance to music and sing. extensive studies have been conducted on musical terms in hafez works; there are some words in his poems that are surrounded by a musical halo, however theirlexical meanings are still considered through the context of the poems, but nobody can get a profound understanding out of hafez’s artistic elegance...

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