Deployment of Rasta-plp with the Siemens Zt Speech Recognition System
نویسنده
چکیده
RelAtive SpecTral Analysis-Perceptual Linear Prediction (RASTA-PLP) is the standard speech feature extraction method used at the International Computer Science Institute. There it has been used primarily in conjunction with a hybrid Artiicial Neural Network (ANN) and Hidden Markov Model (HMM) speech recognition system. This work explores the viability of the RASTA-PLP as a candidate feature extraction method in the Siemens ZT recognition system. Experiments with a basic RASTA-PLP setup connrm that it provides good performance and is a potentially useful tool which merits further research and experimentation.
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