Abstract
In this study, vector quantization and hidden Markov models were used to achieve speech command recognition. Pre-emphasis, a hamming window, and Mel-frequency cepstral coefficients were first adopted to obtain feature values. Subsequently, vector quantization and HMMs (hidden Markov models) were employed to achieve speech command recognition. The recorded speech length was three Chinese characters, which were used to test the method. Five phrases pronounced mixing various human voices were recorded and used to test the models. The recorded phrases were then used for speech command recognition to demonstrate whether the experiment results were satisfactory.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call