Endpoint detection is very important undertaking on the side of getting a good understanding and figuring out if a plasma etching process is done in the right way, especially if the etched area is very small (0.1%). It truly is a crucial part of supplying repeatable effects in every single wafer. When the film being etched has been completely cleared, the endpoint is reached. To ensure the desi...

For automatic speech recognition, endpoint detection is required to isolate the speech of interest so as to be able to create a speech pattern or template. The process of separating the speech segments of an utterance from the nonspeech segments obtained during the recording process is called endpoint detection. In this paper, we present new endpoint detection algorithm based on high order stat...

In plasma etching processes it is critical to know when the film being etched has cleared to the underlying film, i.e. to detect endpoint, in order to achieve the desired device performance in the resulting integrated circuit. The most highly utilized sensor technology for determining endpoint has historically been optical emission spectroscopy (OES), because it is both non-invasive and highly ...

In this paper, we discuss the possibility of applying weighted finite state transducer (WFST) as a unified framework to solve endpoint detection problem. In general, endpoint detection is composed of two cascaded decision processes. The first process is voice activity detection (VAD) which makes framelevel speech/non-speech classification. The second process is utterance-level detection which m...

The paper deals with the use of dynamic programming for word endpoint detection in isolated word recognition. Endpoint detection is based on likelihood maximization. Expectation maximization approach is used to deal with the problem of unknown parameters. Speech signal and background noise energy is used as features for making decision. Performance of the proposed approach was evaluated using i...

It is found that the detection using basic spectral entropy becomes difficult and inaccurate when speech signals are contaminated by high noise. This paper presents an improved entropy-based algorithm. The way to compute spectral probability density function of entropy is altered by the introduction of a positive constant. The modification improves the discriminability between speech and noise ...

The most commonly used technique for water content determination is Karl-Fischer titration with electrometric detection, requiring specialized equipment. When appropriate equipment is not available, the method can be performed through visual detection of a titration endpoint, which does not enable an analysis of colored samples. Here, we developed a method with spectrophotometric detection of a...