Speech is the nature's gift to the human being which contributes towards the intelligence and discrimination from rest of the animal kingdom. Taking into consideration technological aspects, speech recognition is the buzzword today, as communication and hands free computing evolving day by day. Speech is a very important mode of the communication and interaction with the digital computer. Speech recognition along with the wide range of applicability in domain of computer science, medical science, psychology, sports, neurology has many challenges while developing. Developing real time speech recognizer may hurdle from adverse environment to anatomy of the human body. It also involves linguistic aspects too. This paper explores various challenges in developing a robust ASR system.
This paper applies wavelet analysis to speech compression. A mother or basis wavelet is first chosen for the compression. The signal is then decomposed to a set of scaled and translated versions of the mother wavelet. The resulting wavelet coefficients that are insignificant or close to zero are truncated achieving signal compression. Analysis of the compression process was performed by comparing the compressed-decompressed signal against the original. This was conducted to determine the effect of the choice of mother wavelet on the speech compression. The results however showed that regardless of bases wavelet used the compression ratio is relatively close to one another.
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