Reconocimiento robusto del habla en presencia de ruido de coche

The performance of existing speech recognition systems degrades rapidly in the presence of background noise when training and testing cannot be done under the same ambient conditions. The aim of this paper is to report the application of several robust techniques on a system based on the HMM (Hidden Markov Models) and VQ (Vector Quatization) approaches for speech recognition in car environment optimization of spectral model order and cepstral lifter, parameterizatrion based on the AR modeling of the autocorrelation sequence -proposed by the authors in [1]-, use of dynamic information and multilabeling.Peer ReviewedPostprint (published version