Abstract: A tornado recognition system converts a sound signal containing a weather-indicating component and a noise component into a probability of a presence of a tornado. The sound signal is transformed from a time domain into a frequency domain and compared with a set of previously developed Markov models of possible signals representative of a presence of the tornado. Next a determination is made by using Virterbi beam search of the probable presence of the tornado. The probability is used to inform of the presence of a tornado.

Abstract: A method and system for converting a sound signal containing a speech component and a noise component into recognizable language are disclosed, wherein the sound signal is transformed from a time domain into a frequency domain. Next the transformed signal is compared with a set of models of all possible sound signals to find a closest-matching known sound signal. A filter is then applied to the transformed signal. Here the filter corresponds to the model of the closest-matching known sound signal. Next a determination is made of an identity of the speech by searching a set of control data models to match a data model with the filtered transformed signal. Finally, a text stream representative of the determination is output, which enables a user not only to hear what may be a noisy voice message, but also to read the filtered message in some form, such as printed text or on a display screen.