Abstract:
This dissertation details the implementation of a real-time, speaker-independent telephone auto attendant from first principles on limited quality speech data. An auto attendant is a computerized agent that answers the phone and switches the caller through to the desired person's extension after conducting a limited dialogue to determine the wishes of the caller, through the use of speech recognition technology. The platform is a computer with a telephone interface card. The speech recognition engine uses whole word hidden Markov modelling, with limited vocabulary and constrained (finite state) grammar. The feature set used is based on Mel frequency spaced cepstral coefficients. The Viterbi search is used together with the level building algorithm to recognise speech within the utterances. Word-spotting techniques including a "garbage" model, are used. Various techniques compensating for noise and a varying channel transfer function are employed to improve the recognition rate. An Afrikaans conversational interface prompts the caller for information. Detailed experiments illustrate the dependence and sensitivity of the system on its parameters, and show the influence of several techniques aimed at improving the recognition rate.
