| Summary: | This research paper aims to develop an isolated-word
automatic speech recognition (IWASR) system based on Vector
Quantization (VQ). This system receives, analyzes, searches and matches an input speech signal with the trained set of speech signals which are stored in the database/codebook, and returns matching results to users. IWASR is meant to assist customers calling a university’s telephone operator to respond to their enquiries in a convenient way using their natural speech. Callers are assisted to select language, faculty and the staff name they wish to contact. To extract features from speech signals, Mel-Frequency Cepstral Coefficients (MFCC) algorithm was applied.
Subsequently, Vector Quantization was used for all feature
vectors generated from the MFCC. A codebook was resulted from training the VQ initial codebook and experimental results showed that the recognition rate has been improved with the increase of codebook size and showed that the codebook size of 81 feature vectors had a recognition rate exceeded 85%.
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