Abstract: The invention provides a method for detecting music in audio speech processing by decomposing an audio signal into component signals in one or more bandwidths. The invention then detects energy levels across preselected time and frequency windows within the narrowest bandwidth components. A predetermined number of detections at predetermined detection levels will result in the likely characterization of music being present in that window.

Abstract: The invention provides a method for detecting phonation style in dynamic communication environments and making software control decisions based on phonation styles enabling an audio message to be classified based on the phonation style such as, but not limited to: normal phonation, whispered phonation, softly spoken speech phonation, high-level phonation, babble phonation, and non-voice sounds. The purpose of the invention is to introduce the phonation style as a way to control computer software.

Abstract: Method and apparatus for the classification of speech signals. Speech is classified into two broad classes of speech production—whispered speech and normally phonated speech. Speech classified in this manner will yield increased performance of automated speech processing systems because the erroneous results that occur when typical automated speech processing systems encounter non-typical speech such as whispered speech, will be avoided.

Abstract: Method for embedding a covert message within a digital audio signal. The existence of the covert message is undetectable and the information content of the covert message can be further rendered unascertainable. Covert message data is embedded within a digital audio signal on an audio frame-by-audio frame basis. Covert message data is embedded either at a rate of one bit per frame or two bits per frame. The invention has uses including but not limited to watermarking digital audio signals, hiding data within a digital audio signal, increasing the channel capacity of a communications channel by placing multiple messages within each other, and generally increasing message robustness.

Abstract: Method for improving speaker identification by determining usable speech. Degraded speech is preprocessed in a speaker identification (SID) process to produce SID usable and SID unusable segments. Features are extracted and analyzed so as to produce a matrix of optimum classifiers for the detection of SID usable and SID unusable speech segments. Optimum classifiers possess a minimum distance from a speaker model. A decision tree based upon fixed thresholds indicates the presence of a speech feature in a given speech segment. Following preprocessing, degraded speech is measured in one or more time, frequency, cepstral or SID usable/unusable domains. The results of the measurements are multiplied by a weighting factor whose value is proportional to the reliability of the corresponding time, frequency, or cepstral measurements performed. The measurements are fused as information, and usable speech segments are extracted for further processing.

Abstract: Method and apparatus for the classification of speech signals. Speech is classified into two broad classes of speech production—whispered speech and normally phonated speech. Speech classified in this manner will yield increased performance of automated speech processing systems because the erroneous results that occur when typical automated speech processing systems encounter non-typical speech such as whispered speech, will be avoided.