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In this paper, noise estimation based on series expansion of orthogonal functions is proposed. The proposed method searches speechless frequency regions and estimates the noise spectrum from the searched speechless frequency regions. The proposed method can adapt to changing of noise power without estimation delay. Experimental results show that the proposed method provides a good performance against...
Speech signal quality is of fundamental importance for accurate speaker identification. The reliability of a speech biometry system, in fact, is known to depend on the amount of material available, in particular on the number of vowels present in the sequence being analysed and on the quality of the signal. This paper highlights the performance of two Signal-to-Noise Ratio (SNR) estimation methods...
While most speech enhancement algorithms improve speech quality, they do not improve speech intelligibility in noise. The reasons for that remain unclear. In this paper, we present a theoretical framework that can be used to analyze potential factors influencing the intelligibility of processed speech. It is hypothesized that if distortions are properly controlled, then large gains in intelligibility...
In real-world environments, the signals captured by a set of microphones in a speech communication system are mixtures of the desired signal, interference, and ambient noise. A promising solution for proper speech acquisition (with reduced noise and interference) in this context consists in using the linearly constrained minimum variance (LCMV) beamformer to reject the interference, reduce the overall...
An algorithm suitable for voice activity detection under reverberant conditions is proposed in this paper. Due to the use of far-filed microphones the proposed solution processes speech signals of highly-varying intensity and signal to noise ratio, that are contaminated with several echoes. The core of the system is a pair of Hidden Markov Models, that effectively model the speech presence and speech...
Formant frequency is a one of the most important speech feature, which has widespread applications in speech recognition, synthesis, and compression. In this paper, a new time-frequency domain scheme for the estimation of formant frequencies from noise-corrupted speech signals is presented. In order to overcome the adverse effect of noise, instead of conventional autocorrelation function (ACF), a...
In the current work, a novel analog hardware to denoise speech signals has been proposed and simulated in 0.5 mum VLSI technology. The system is based on Automatic Gain Control which suppresses the noisy parts while boosting clean intervals of a signal. Further, the architecture is devised using Operational Transconductance Amplifiers (OTA) operating in sub-threshold region for attaining high programmability,...
Accurate endpoint detection is important for speech procession. The endpoint detection problem is nontrivial for non-stationary backgrounds where noises may be introduced by the speaker, the recording environment and the transmission system. In this paper, an effective endpoint detection algorithm is proposed for improving speech signal processing performance in noisy environment. The proposed speech/pause...
We consider the problem of word boundary detection in spontaneous speech utterances. Acoustic features have been well explored in the literature in the context of word boundary detection; however, in spontaneous speech of Switchboard-I corpus, we found that the accuracy of word boundary detection using acoustic features is poor (F-score ~ 0.63). We propose a new feature - that captures lexical cues...
Despite the success of recent speech enhancement algorithms, the enhanced signals still suffer from undesirable speech distortion caused by over-attenuation of weak speech spectral components. In this paper, a post-processing technique based on the regeneration of both voiced and unvoiced speech is proposed to alleviate this problem. A non-linear transformation is first applied to a Wiener filtered...
This paper presents a speech enhancement method based on an analysis-synthesis framework using harmonic noise model (HNM) in car noise environment. The major advantages of this method are effective suppression of car noise even in very low signal-to-noise ratio environments and mitigation of ldquomusical tonesrdquo which are generally introduced by conventional methods. In this paper, we devise a...
In this paper, we propose a novel algorithm for the separation of convolutive speech mixtures using two-microphone recordings, based on the combination of independent component analysis (ICA) and ideal binary mask (IBM), together with a post-filtering process in the cepstral domain. Essentially, the proposed algorithm consists of three steps. First, a constrained convolutive ICA algorithm is applied...
We investigate a general framework for noise reduction which consists in controlling the level of signal distortion while reducing the level of noise. A parameterized non-causal filter that allows for tuning the signal distortion and noise reduction inversely is obtained and is referred to as parameterized multichannel non-causal Wiener filter (PMWF) herein. The same optimization problem leads to...
In this paper two multichannel noise reduction strategies are compared in the context of binaural hearing aids. Recently a novel noise reduction method based on spatial-temporal prediction (STP) was introduced which showed an improvement over methods based on multichannel Wiener filtering, although at the cost of a higher computational complexity. Whereas this newmethod operates in the time domain,...
This paper introduces an algorithm to separate speech streams from a single-channel speech mixture. Most current speech segregation algorithms allocate speech regions to participating speakers depending on which speaker dominates in which spectro-temporal region. The proposed method is a different approach to speech segregation, in that it separates the participating speaker streams rather than decide...
Perceived quality of the speech signal deteriorates significantly in the presence of ambient noise. In this paper, based on the analysis that the partial masking effect is a main source of the quality degradation when interfering signals are present, we propose a novel approach to enhance the perceived quality of speech signal when the ambient noise cannot be directly controlled by reinforcing it...
In this paper, we reveal new findings about the generated musical noise in minimum mean-square error short-time spectral amplitude (MMSE STSA) processing. Recently we have proposed a objective metric of musical noise based on kurtosis change ratio on spectral subtraction (SS). Also we found an interesting relationship among the degree of generated musical noise, the shapes of signal-s probability...
The purpose of this study is to investigate the performance of speech presence (SP) microphone array beamforming. When the presence uncertainty of the desired speech is considered, noise reduction is greatly achieved while preserving low speech distortion level. Furthermore, we propose a novel model based speech presence probability (SPP) estimator, exploring both the sinusoid structure of speech...
Monaural speech segregation is a very challenging problem which has been studied by many researchers. In this paper, we focus on voiced speech segregation. Different strategies are used to segregate resolved and unresolved harmonics respectively. For resolved harmonics, "harmonicity" principle and a novel mechanism based on "minimum amplitude" principle are employed. Amplitude...
Unvoiced speech poses a big challenge to current monaural speech segregation systems. It lacks harmonic structure and is highly susceptible to interference due to its relatively weak energy. This paper describes a new approach to segregate unvoiced speech from nonspeech interference. The system first estimates a voiced binary mask, and then performs unvoiced speech segregation in two stages: segmentation...
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