In this paper, a voice activity detector (VAD) for variable rate speech coding is decomposed into two parts, a decision rule and a background noise statistic estimator, which are analysed separately by applying a statistical model. A robust decision rule is derived from the generalized likelihood ratio test by assuming that the noise statistics are known a priori. To estimate the time-varying n...

On speech signal processing, it is very important to find the fundamental frequency of voice. The reason is why it is used in variable places, such as speech-enhancement-system, speech-recognition system, speakerclassification-system, and handicapped assisting-system. However the pitch detection is difficult when the original signal is corrupted by noise, or put in transition section of voice. ...

The role of the statistical model-based voice activity detector (SMVAD) is to detect speech regions from input signals using the statistical models of noise and noisy speech. The decision rule of SMVAD is based on the likelihood ratio test (LRT). The LRT-based decision rule may cause detection errors because of statistical properties of noise and speech signals. In this article, we first analyz...

This paper brings an improvement of voice activity detection, based on vector quantization and speech enhancement preprocessing (VQ-VAD) proposed recently, and applied to speaker verification system under noisy environment. VQ-VAD is based on computing the likelihood ratio on an utterance-by utterance basis from mel-frequency cepstral coefficients that train speech and non-speech models. Wherea...

This paper addresses the problem of segmenting audio data recorded with embedded devices for the purpose of intelligent sensing in the context of multi-modal interactions. We propose a real-time method for robust speech detection in natural, noisy environments. It is based on a fusion of high order statistics of the LPC residual and autocorrelation, and adopts an on-line version of Expectation ...

Nowadays, the accuracy of speech processing systems is strongly affected by acoustic noise. This is a serious obstacle regarding the demands of modern applications. Therefore, these systems often need a noise reduction algorithm working in combination with a precise voice activity detector (VAD). The computation needed to achieve denoising and speech detection must not exceed the limitations im...

In this paper, a Voice Activity Detector (VAD) is proposed for smart hearing protection applications where speech is to get through the hearing protector while ambient noise is to be blocked out. The VAD calculates a short-term statistical assessment of the temporal envelopes within different frequency bands. This assessment uses the Inter-Quartile Range (IQR) and reflects the dispersion of the...

Discontinuous transmission based on speech/pause detection represents a valid solution to improve the spectral efficiency of new-generation wireless communication systems. In this context, robust Voice Activity Detection (VAD) algorithms are required, as traditional solutions present a high misclassification rate in the presence of the background noise typical of mobile environments. This paper...

− This paper presents the development of integrated near-end acoustic echo and noise reduction algorithm. The modified frequency-sampling filter (FSF) provides an effective filterbank for splitting signal into equally spaced frequency channels. The center clipper and attenuator are employed at each frequency bin for attenuating near-end acoustic echo and noise. The adaptive clipping threshold a...

Separating technique for singing voice from music accompaniment is very useful in original sound type Karaoke instrument. We propose a real-time system to separate singing voice from music accompaniment for stereo recordings. Proposed algorithm consists of two stages. The first stage is a spectral change detector. The last stage is a selective vocal separation in frequency bins. Listening tests...