Speech enhancement and features compensation algorithms for continuous speech recognition

The degradation of the speech signal due to adverse conditions generates low accuracy rates in speech recognition systems. The authors propose mixing two methods: pre-extraction of features for speech enhancement and post-extraction of features for features compensation. According to their main focus, they are fundamentally oriented to minimize the misfit caused by noise insertion in the speech signal. These methods will be applied before and after the extraction of features, respectively, therefore allowing the best possible estimation of the clear signal from its degraded version.