Voice-controlled devices provide a smart solution to operate addon appliances in a car. Although, speech recognition appears as a key technology to produce useful end-user interfaces, the amount of acoustic disturbances existing in automotive platforms usually prevents satisfactory results. In most of the cases, noise reduction techniques involving a Voice Activity Detector (VAD) are required. ...

An effective speech event detector is presented in this work for improving the performance of speech processing systems working in noisy environment. The proposed method is based on a trained support vector machine (SVM) that defines an optimized non-linear decision rule involving the subband SNRs of the input speech. It is analyzed the classification rule in the input space and the ability of ...

The problem of signal detection using a flexible and general model is considered. Due to applicability and flexibility of sparse signal representation and approximation, it has attracted a lot of attention in many signal processing areas. In this paper, we propose a new detection method based on sparse decomposition in a union of subspaces (UoS) model. Our proposed detector uses a dictionary th...

•Finds regions of quiet speech using the noise estimate and scales these regions using α = 0.99 to avoid noise amplification for low SNR’s •Identifies if the high amplitudes of the frame will be clipped after scaling and reduces the scale factors accordingly Key Aspects of the Volume Leveler •Tracks the noise level when the Voice Activity Detector(VAD) does not detect speech, so pure noise regi...

This paper proposes a voice activity detector (VAD) based on the complex Laplacian model. With the use of a goodness-of-fit (GOF) test, it is discovered that the Laplacian model is more suitable to describe noisy speech distribution than the conventional Gaussian model. The likelihood ratio (LR) based on the Laplacian model is computed and then applied to the VAD operation. According to the exp...

This paper presents a noise reduction method for speech communication where the input signal is divided into a number of subbands that are individually weighted in time domain according to the short time Signal-to-Noise Ratio estimate (SNR) in each subband at every time instant. Instead of focusing on suppression the noise, the method is focusing on speech enhancement. The method has proven to ...

Audio-visual speech source separation consists in mixing visual speech processing techniques (e.g. lip parameters tracking) with source separation methods to improve and/or simplify the extraction of a speech signal from a mixture of acoustic signals. In this paper, we present a new approach to this problem: visual information is used here as a voice activity detector (VAD). Results show that, ...