This paper shows an efficient voice activity detector (VAD) that is based on the estimation of the long-term spectral divergence (LTSD) between noise and speech periods. The proposed method decomposes the input signal into overlapped speech frames, uses a sliding window to compute the long-term spectral envelope and measures the speech/non-speech LTSD, thus yielding a high discriminating decisi...

In this paper, we present a word counting method that enables speech recognition systems to perform reliable barge-in detection and also make a fast and accurate determination of end of speech. This is achieved by examining partial recognition hypotheses and imposing certain “word stability” criteria. Typically, a voice activity detector is used for both barge-in detection and end of speech det...

A robust voice activity detector (VAD) is expected to increase the accuracy of ASR in noisy environments. This study focuses on how to extract robust information for designing a robust VAD. To do so, we construct a noise eigenspace by the principal component analysis of the noise covariance matrix. Projecting noise speech onto the eigenspace, it is found that available information with higher S...

We propose a general methodology to design a robust voice activity detector that suits the needs of the speech enhancement system it is dedicated to. More than imposing rules, we initiate ideas on how to perform the analysis of the requirements for the Voice Activity Detection (VAD) and how to choose a reference, and evaluate the performances of the explored solutions in order to choose the one...

Acoustic source localization system for speech signals based on five microphone array was developed. Three dimensional position computation is based on time delay estimation between pairs of microphones. The psyhoacoustically motivated voice activity detector was used to robustly determine activity of speaker in presence of background noise. The detector was based on modulation properties of hu...

This paper deals with the problem of voice activity detection in adverse acoustic conditions, namely high and varying noise scenarios. For robotic applications, we need the voice activity detector to be computationally light, robust to varying levels of background noise, and have a low latency, especially if we are tracking moving speakers. We analyze three voice activity detectors—two model th...

In this work, we present an algorithm that switches between the energy and the entropy based voice activity detectors (VADs) to provide an improved performance under varying signal to noise ratio (SNR) conditions. The motivation for switching has come from the observed complementary behavior in the noise estimation performances of energy and entropy based voice activity detectors when evaluated...

In this paper, a fixed point Variable Bit-Rate (VBR) Mixed Excitation Linear Predictive Coding (MELP TM ) vocoder is presented. The VBR-MELP vocoder is also implemented on a TMS320C54x and it achieves virtually indistinguishable federal standard MELP quality at bit-rates between 1.0 to 1.6 kb/s. The backbone of VBRMELP vocoder is similar to that of federal standard MELP. It utilizes a novel sub...