Accurate gender classification is useful in speech and speaker recognition as well as speech emotion classification, because a better performance has been reported when separate acoustic models are employed for males and females. Gender classification is also apparent in face recognition, video summarization, human-robot interaction, etc. Although gender classification is rather mature in a...

Speech quality and intelligibility might signi cantly deteriorate in the presence of background noise, especially when the speech signal is subject to subsequent processing. In this paper we represent a class of Kalmanlter based speech enhancement algorithms with some extensions, modi cations, and improvements. The rst algorithm employs the estimate-maximize (EM) method to iteratively estimate ...

This research is directed toward transforming a speech signal into a new speechlike signal that is perceived as identical to the original signal in all respects except that it is articulated at a rate different from that of the original speech. Such a technique is of interest in a variety of applications including learning a second language, developing talking books for the blind, generation of...

Speech is one of the ways to express ourselves naturally. So, speech can be used as a means to communicate with machines. In this work, using MATLAB as a platform isolated word recognizer is achieved. Speech signals get distorted by many kinds of noises. Hence, it is necessary to reduce the noise contained in the speech signal. This is called speech enhancement. Speech enhancement aims at impro...

This paper investigates the problem of automatic segmentation of speech recorded in noisy channel corrupted environments. Using an HMM-based speech segmentation algorithm, speech enhancement and parameter compensation techniques previously proposed for robust speech recognition are evaluated and compared for improved segmentation in colored noise. Speech enhancement algorithms considered includ...

This paper proposes a novel method of speech enhancement using tensor factorization, which is extended from complex non-negative matrix factorization (CMF), in the modulation frequency domain. Non-negative matrix factorization (NMF) has attracted a great deal of attention as a recent approach to speech enhancement for its ease of feature detection in the acoustic frequency domain. However, prev...

Speech is most effective and natural medium to exchange the information among people. The speech system also goes under the process of some software tools to present the information in effective way. This kind of effectiveness is defined as the translation of the information to text or some other speech form. In speech communication, the speech signal is always accompanied by some noise. Theref...

Most noisy speech enhancement methods result in partial suppression and distortion of speech spectrum. At instances when the local signal-to-noise ratio at a frequency band is very low speech partials are often obliterated. In this paper a method for enhancement and restoration of noisy speech based on a harmonic-noise model (HNM) is introduced. A HNM imposes a temporal-spectral structure that ...

Most noisy speech enhancement methods result in partial suppression and distortion of speech spectrum. At instances when the local signal-to-noise ratio at a frequency band is very low speech partials are often obliterated. In this paper a method for enhancement and restoration of noisy speech based on a harmonic-noise model (HNM) is introduced. A HNM imposes a temporal-spectral structure that ...

Periodogram smoothing of the received noisy signal is a challenging problem in speech enhancement. We present a Bayesian approach, where the instantaneous periodogram is smoothed through an adaptive smoothing parameter. By updating sufficient statistics using new samples of the noisy signal, the smoothing parameter is adjusted on-line. The performance of the novel smoothing algorithm is studied...