Voice Activity Detectors (VAD's) are widely used in speech technology applications where available transmission or storage capacity is limited (e.g. mobile, DCME, etc.) and must be utilised with maximum economy. Modern day digital speech coding algorithms can provide toll quality speech at bit-rates as low as 8kbit/s (e.g. ITU-T G.729) and the use of a VAD can achieve further economy in average...

We present an experimental analysis of on-off patterns in Voice over IP (VoIP), where we study the talk-spurt/gap distribution produced by two modern silence detectors: ITU G.729 Annex B Voice Activity Detector (VAD) and NeVoT Silence Detector (SD). The results indicate that spurt/gap distributions are fairly sensitive to both the sound volume and the type of silence detectors, but all of them ...

This paper presents some up-to-date audio processing techniques which have been developed and integrated into the University of Colorado (CU) communicator system. The CU Communicator is an interactive human-machine dialogue system for airline, hotel and rental car information. The baseline system was fully functional in June 1999. Since then, many improvements have been made. The paper will con...

In an online automatic speech recognition system, the role of the endpoint detector is to infer when a user has finished speaking a query. Accurate and low-latency endpoint detection is crucial for natural voice interaction. Classic voice activity detector (VAD) based approaches monitor the incoming audio and trigger when a sufficiently long pause is detected. Such approaches are typically limi...

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. The Fuzzy ...

Speech constitutes much of the communicated information; most other perceived audio signals do not carry nearly as much information. Indeed, much of the non-speech signals maybe classified as ‘noise’ in human communication. The process of separating conversational speech and noise is termed voice activity detection (VAD). This paper describes a new approach to VAD which is based on the Wavelet ...

This paper develops, simulates and experimentally evaluates a novel method based on non-contact low frequency ultrasound which can determine, from airborne reflection, whether the lips of a subject are open or closed. The method is capable of accurately distinguishing between open and closed lip states through the use of a low complexity detection algorithm, and is highly robust to interfering ...

This paper introduces the use of machine learning to improve efficiency of ultra-low-power sensor interfaces. Adaptive feature extraction circuits are assisted by hardware embedded learning to dynamically activate only most relevant features. This selection is done in a context and power cost-aware way, through modification of the C4.5 algorithm. Furthermore, context dependence of different fea...

In this paper, we describe the design procedure for a wireless communication interactive voice response system. The application must work in a very noisy environment which has imposed many design constraints. We will address the sensible aspects of three components of the application: the voice activity detector (VAD), the automatic speech recognition (ASR) system, and the confidence measure (C...