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1) There are certain operational difficulties associated with speech recognition.

2) Possible applications are continuous speech recognition and commands to robot arms.

3) The new speech recognition system is not absolutely foolproof, but it is a huge breakthrough.

4) Despite a large amount of research into automatic speech recognition the results have been unimpressive.

5) Noisy Environments: speech recognition is made difficult if interference is created by noisy machinery or extraneous conversations.

6) Areas such as vision, continuous speech recognition and synthesis, and machine learning have been hard.

7) The ability of speech recognition systems to discriminate words from acoustic information alone is not encouraging.

8) Currently available speech recognition systems impose a selection of constraints on the input to simplify the speech recognition task.

9) For speech recognition the principal operational difficulty to be faced is the interference to the acoustic signal from background noise.

10) Continuous speech recognition and synthesis are additional examples of tasks neural networks are undertaking with reasonable success.

11) A commonly used argument in favour of speech recognition is that it is the most natural communication medium.

12) An isolated - word speech recognition system based on HMM has been established.

13) In terms of the speech recognition technology, speaker independent large vocabulary continuous speech recognition has been realized, and is fighting into way from laboratory to industrial application.

14) The research on Automatic Speech Recognition has seen great achievement in the passed twenty years.

15) This paper presents an audiovisual continuous speech recognition system for noise environments.

16) Speech recognition has a wide application future. It has made a full application in dictation machine, telephone inquiry system and home application control etc.

17) A crucial issue in triphone-based continuous speech recognition is the large number of parameters to be estimated against the limited availability of training data.

18) One example is the method of recognition using template matching which is applied in both speech recognition and optical character recognition.

19) Jelinek took individual words as the states in his Markov model for speech recognition.

20) Its use has been recognised to be of value in applications such as machine translation and speech recognition.

21) What you hear will incorporate high-fidelity sound, speech synthesis, and speech recognition.

22) Our first aim was to examine the lexical access components of a number of existing speech recognition systems.

23) Indeed, in the later chapters we will show that this is impractical for any relatively unconstrained speech recognition system.

24) Writing allows private communication with the computer that is not possible with speech recognition.

25) MPEG, PCs with multiple CD - ROM drives, and speech recognition are, " absolutely breathtaking. "

26) This paper raised a method of pattern recognition, it can be used to the continuous speech recognition with reference, text understanding and data file analysis.

27) As for the phenomenon of coarticulation, which is a difficult problem in the field of speech recognition,(http://sentencedict.com/speech recognition.html) the results in this article can be seen as a fundamental exploration.

28) In this paper, error tolerant techniques are studied for large vocabulary speaker independent Chinese continuous speech recognition and understanding systems.

29) The experiment result reveals this system has high recognition rate and fast recognition speed. So this system is an effective hardware realizing technique of automatic speech recognition device.

30) The application of Artificial Neural Networks ( ANN ) to Automatic Speech Recognition ( ASR ) is investigated in this thesis.