Abstract:
Many application environments have already used
speech interface. But the low speech recognition rate
makes it difficult to extend its application to new
fields. In the human-computer interaction through
spoken dialogue are being investigated. Automatic
Speech recognition (ASR) is the process of converting
a spoken speech into text that can be manipulated by
the computer. The state of the art in automatic speech
recognition has reached the point that searching for
and extracting information from large speech
repositories. This system presents semantic-oriented
approach to correct both semantic and lexical errors,
which is also more accurate for especially domainspecific
speech error correction. This paper
demonstrates the superior performance of this
approach and some advantages over previous lexicaloriented
approaches by comparing such approaches.
Experiments carried out on various speeches in
English syllable indicated a successful decrease in the
number of errors and an improvement in overall error
correction rate.
