Speech Coding and Recognition

This paper investigates the performance of a speech recognizer in an interactive voice response system for various coded speech signals, coded by using a vector quantization technique namely Multi Switched Split Vector Quantization Technique. The process of recognizing the coded output can be used in Voice banking application. The recognition technique used for the recognition of the coded speech signals is the Hidden Markov Model technique. The spectral distortion performance, computational complexity, and memory requirements of Multi Switched Split Vector Quantization Technique and the performance of the speech recognizer at various bit rates have been computed. From results it is found that the speech recognizer is showing better performance at 24 bits/frame and it is found that the percentage of recognition is being varied from 100% to 93.33% for various bit rates.

Authors:

• M. Satya Sai Ram
• P. Siddaiah
• M. Madhavi Latha

Keywords:

• Linear predictive coding
• Speech Recognition
• Voice banking
• Multi Switched Split Vector Quantization
• Hidden Markov Model
• Linear Predictive Coefficients.

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