15. A method of recognizing emotional states in a voice of a telephone caller, the method comprising: providing a first plurality of voice samples; obtaining a second plurality of voice samples of a telephone caller, from a telephone call; identifying each sample of said pluralities of samples as belonging to a predominant emotional state; dividing each sample into at least one of frames, subframes, and segments; extracting at least one acoustic feature for each sample of the pluralities of samples; calculating statistics of the speech samples from the at least one feature; classifying an emotional state in the first plurality of samples with at least one neural network; training the at least one neural network to recognize an emotional state from the statistics by comparing the results of identifying and classifying for the first plurality of samples; classifying an emotion in the second plurality of voice samples obtained from a telephone call with the at least one trained neural network; storing the voice samples and the emotional states in a storage medium, in a manner to allow later retrieval of the stored voice samples and emotional states; outputting in a human-recognizable format an indication of the emotional state of the telephone caller; and routing the call containing said voice samples to at least one predetermined location according to the at least one classified emotional state.
15. A method of recognizing emotional states in a voice of a telephone caller, the method comprising: providing a first plurality of voice samples; obtaining a second plurality of voice samples of a telephone caller, from a telephone call; identifying each sample of said pluralities of samples as belonging to a predominant emotional state; dividing each sample into at least one of frames, subframes, and segments; extracting at least one acoustic feature for each sample of the pluralities of samples; calculating statistics of the speech samples from the at least one feature; classifying an emotional state in the first plurality of samples with at least one neural network; training the at least one neural network to recognize an emotional state from the statistics by comparing the results of identifying and classifying for the first plurality of samples; classifying an emotion in the second plurality of voice samples obtained from a telephone call with the at least one trained neural network; storing the voice samples and the emotional states in a storage medium, in a manner to allow later retrieval of the stored voice samples and emotional states; outputting in a human-recognizable format an indication of the emotional state of the telephone caller; and routing the call containing said voice samples to at least one predetermined location according to the at least one classified emotional state. 16. The method of claim 15 , wherein the calls containing the voice samples are routed to at least one location selected from the group consisting of a voice-mail center, a call center, an e-mail destination, a customer service center, a manager, and emergency response personnel.