Computationally efficient voice dialing system

Subband based feature parameters are becoming widely used for speech recognition purposes. In this thesis a subband-based, small-vocabulary, speaker-dependent, isolated-word recognition system is proposed. The most distinctive property of the proposed system is its low computational cost which enables it to run at real-time on a simple microcontroller. The system is used as the core of a voice dialer which is designed to work together with Karel switchboxes. In training section first, an energy-based endpoint (startingpoint) detection method is applied for speech detection. Then feature extraction is applied on a fixed length, pcm-quantized (a-law) speech long enough to cover a single word. In recognition section template matching is used to find the most likely vocabulary element. A recognition rate of 93% is obtained in the simulations.