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文章基本信息

  • 标题:Speech Recognition
  • 作者:Anjali Kalra ; Sarbjeet Singh ; Sukhvinder Singh
  • 期刊名称:International Journal of Computer Science and Network Security
  • 印刷版ISSN:1738-7906
  • 出版年度:2010
  • 卷号:10
  • 期号:6
  • 页码:216-221
  • 出版社:International Journal of Computer Science and Network Security
  • 摘要:Language is man's most important means of communication and speech its primary medium. Speech provides an international forum for communication among researchers in the disciplines that contribute to our understanding of the production, perception, processing, learning and use. Spoken interaction both between human interlocutors and between humans and machines is inescapably embedded in the laws and conditions of Communication, which comprise the encoding and decoding of meaning as well as the mere transmission of messages over an acoustical channel. Here we deal with this interaction between the man and machine through synthesis and recognition applications. The paper dwells on the speech technology and conversion of speech into analog and digital waveforms which is understood by the machines. Speech recognition, or speech-to-text, involves capturing and digitizing the sound waves, converting them to basic language units or phonemes, constructing words from phonemes, and contextually analyzing the words to ensure correct spelling for words that sound alike. Speech Recognition is the ability of a computer to recognize general, naturally flowing utterances from a wide variety of users. It recognizes the caller's answers to move along the flow of the call. We have emphasized on the modeling of speech units and grammar on the basis of Hidden Markov Model. Speech Recognition allows you to provide input to an application with your voice. The applications and limitations on this subject has enlightened us upon the impact of speech processing in our modern technical field. While there is still much room for improvement, current speech recognition systems have remarkable performance.
  • 关键词:Speech Technology; Hidden Markov Model
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