Noise compensation for speech recognition in car noise environments
Ruikang Yang, Petri Haavisto · 2002
A noise compensation algorithm for HMM based speech recognition systems, which utilizes the parallel model combination concept, is presented. The algorithm was tested using the TIDIGITS database with artificially added car noise. Very promising results were obtained. The results show that at -10 dB SNR the recognition accuracy could be improved from 34% to 89%. The noise compensation algorithm was also tested using a database which was recorded in a car. Improved performance was obtained, but the improvement; was clearly smaller than with the artificially added noise.