Sentence examples for more automatic speech from inspiring English sources

We also investigate the effectiveness of using more automatic speech recognition (ASR) hypotheses (n-best lists) to extract lexical features.

This last issue has been tackled in the more general framework of automatic speech recognition (ASR) system robustness; most of the proposed methods operate at the signal level or at the acoustic model level.

Each A-STAR member contributed one or more of the following spoken language technologies: automatic speech recognition, machine translation, and text-to-speech through Web servers.

Automatic speech recognition is becoming more ubiquitous as recognition performance improves, capable devices increase in number, and areas of new application open up.

With the fast development of mobile internet, hands-free speech interaction with automatic speech recognition (ASR) system is natural and becoming more and more popular.

Recent research on the TIMIT corpus suggests that longer-length acoustic models are more appropriate for pronunciation variation modelling than the context-dependent phones that conventional automatic speech recognisers use.

For better VC performance, the VC technique needs to train more complex nonlinear features, such as Mel Cepstral Coefficients (MCC) [10], which are widely used in automatic speech and speaker recognition.

For example, there is a growing interest in developing useful systems for automatic speech recognition (ASR) in different noisy environments [5, 6], and most of these studies are focused on developing more robust VAD systems in order to compensate for the harmful effect of the noise on the speech signal.

They founded Sound Intelligence in 2000, initially focussing on speech-noise separation for automatic speech recognition, with a sideline in the analysis of non-speech sounds.

So shoppers might expect even more automatic checkouts, for example.

ASR, automatic speech recognition.