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61) Speech recognition is such a kind of technology that deals with speech signals with computer and recognizes them to symbol sequence.

62) Large vocabulary continuous speech recognition system consists of several components, and recognition errors are caused by different factors.

63) A large quantities of phonetically segmented speech is necessary in speech recognition and speech synthesis.

64) Further more, in present years, audio processing technology developed rapidly and speech recognition technology already grown up and achieve high veracity in vocabulary speech recognition.

65) The training unit is a very important part in speech recognition and it determines the entire properties of the system.

66) The performance of automatic speech recognition decreases drastically for nonnative speakers, especially those who are just beginning to learn foreign language or who have heavy accents.

67) In order the discrimination and robustness of speech recognition system, this thesis does some deeper research.

68) The main advantages of this method is operation simple and save memory, so that it may have higher speed and accuracy for speech recognition.

69) In this paper, the real-time realization of Automatic Speech Recognition (ASR) technology on common platform is investigated.

70) To the sensor , Compound Cepreum Coefficients ( CD - CC ) is proposed Linear Predication Cepreum Coefficients ( LPCC ) in the speech recognition system.

71) This paper addresses the problem of speech recognition under telephone channel conditions using data simulation method and HMM(Hidden Markov Model)adaptation.

72) The speech control robot is to use a single slice machine Be the core parts, ask for help it of speech recognition function to carry out the equipments of the control.

73) The system employs large vocabulary continuous speech recognition engine in front speech input end.

74) An error-tolerant algorithm in decoding module of Mandarin continuous speech recognition is examined to correct substitution, insertion and deletion errors in acoustic recognition.

75) Speech endpoint detection is an important process of speech analysis, speech recognition and speech monitor.

76) Compared with continuous speech recognition, keyword spotting has advantage in increasing the naturalness of the dialogue.

77) Research on speech recognition error detection and correction by natural language understanding (NLU) method will be an important research direction of improving the performance of speech recognition.

78) A speech recognition method based on modified hidden Markov model (MHMM) is presented. The weighted function algorithm is introduced to reduce the error rate of the system.

79) Speech recognition and natural language processing are technologies still in their infancy.

80) A Chinese speech recognition method based on character - based N - gram model is proposed in this thesis.

81) In Mandarin speech recognition, this model shows a better performance and requires less memory space than the word based trigram model.

82) Aiming at the application of speech recognition technology in aspect of controlling machine tool, we introduce the classes, principles and technology of speech recognition simply.

83) In this paper, the real - time realization of Automatic Speech Recognition ( ASR ) technology on common is investigated.

84) The object is to study the students and Automatic Speech Recognition to interested researchers.

85) Speech endpoint detection is a paragraph beginning and end speech analysis, speech synthesis and speech recognition of a necessary link.

86) Experiments on speaker-independent continuous speech recognition demonstrated that the combined model performed much better than both LPHMM and traditional HMM.

87) Speech pattern match is one of the key steps in speech recognition.

88) The longest established of these is automatic speech recognition (ASR),(http://sentencedict.com) the technology that converts the spoken word to text.

89) Privacy issues aside, this practice is critical for improving the quality of speech recognition and for the continued expansion of voice application platforms.

90) This thesis presents work in the area of automatic Speech Recognition (ASR).