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...

When automatic speech recognition (ASR) and speaker verification (SV) are applied in adverse acoustic environments, endpoint detection and energy normalization can be crucial to the functioning of both systems. In low signal-to-noise ratio (SNR) and nonstationary environments, conventional approaches to endpoint detection and energy normalization often fail and ASR performances usually degrade ...

Abstract The research reported in this article is concerned with the question of detecting and subsequently determining endpoint a long-stretch, ultraprecision surface polishing process. While detection has attracted much attention for several decades chemical-mechanical planarization semiconductor wafer processes, uniqueness process under our investigation calls novel solutions. To tackle chal...

In recent years, many improvements have been made in foodborne pathogen detection methods to reduce the impact of food contamination. Several rapid methods have been developed with biosensor devices to improve the way of performing pathogen detection. This paper presents an automated endpoint detection system for amplicons generated by loop mediated isothermal amplification (LAMP) on a microflu...

INTRODUCTION: This study aimed to develop a duplex endpoint PCR assay for rapid detection and differentiation of Leptospira strains. METHODS: Primers were designed to target the rrs (LG1/LG2) and ligB (LP1/LP2) genes to confirm the presence of the Leptospira genus and the pathogenic species, respectively. RESULTS: The assay showed 100% specificity against 17 Leptospira strains with a limit ...

Pre-processing of Speech Signal serves various purposes in any speech processing application. It includes Noise Removal, Endpoint Detection, Pre-emphasis, Framing, Windowing, Echo Canceling etc. Out of these, silence/unvoiced portion removal along with endpoint detection is the fundamental step for applications like Speech and Speaker Recognition. The proposed method uses Probability Density Fu...

This paper describes a robust speech detection algorithm for speech-activated hands-free applications. The system consists of three techniques: (1) noise suppression with efficient implementation, (2) robust endpoint detection and (3) speech verification using garbage modeling and confidence measure. With efficient implementation, noise suppression improves the SNR by roughly 10-20 dB. The endp...