Abstract
This paper presents a novel and efficient audio signal recognition algorithm with limited computational complexity. As the audio recognition system will be used in real world environment where background noises are high, conventional speech recognition techniques are not directly applicable, since they have a poor performance in these environments. So here, we introduce a new audio recognition algorithm which is optimized for mechanical sounds such as car horn, telephone ring etc. This is a hybrid time-frequency approach which makes use of acoustic fingerprint for the recognition of audio signal patterns. The limited computational complexity is achieved through efficient usage of both time domain and frequency domain in two different processing phases, detection and recognition respectively. And the transition between these two phases is carried out through a finite state machine(FSM)model. Simulation results shows that the algorithm effectively recognizes audio signals within a noisy environment.
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