Parallel processing capabilities in the process of speech recognition

Abstract

A Speech recognition is one of the important process of information technology. Speech recognition plays a key role in many systems like voice control, IP-telephony, personal identification, recognition of individual words and phrases, accepting applications for reference services and searching system. There are many researching companies in this area, which developing and improving methods, algorithms and applications for the segmentation of the speech signal and for the calculation of parametric indicators of the selected fragments of the speech signals. In the preliminary stages of speech processing is being implemented algorithms for the allocation of phonetic characteristics, which are subjected to syntactic and semantic analysis in subsequent stages. In isolating the phonetic characteristics of the input speech signals the calculation cepstral characteristics one of the important processes in speech recognition. The Mel-frequency cepstrum is gives good results for isolating phonetic characteristics of speech signals. The calculation of Mel-frequency cepstral coefficients takes a lot of time in speech recognition process. This is clearly evident in real time systems like IP-telephony. The calculation of Mel-frequency cepstral coefficients takes a lot of time in speech recognition process. This is clearly evident in real time systems like a IP-telephony. For the solving these problem we need to create a stream computing. A practical solution of the problem of faster processing is the use of parallel computing algorithms. The hardware platform implementation of parallel algorithms for calculation of Mel-frequency cepstral coefficients can be multi-core processors.