Abstract: Hardware and/or software systems, devices, networks, and methods for identity recognition and verification based on vocal spectrum analysis. The system including one or more processors coupled to a memory/storage to collect audio samples sufficient to generate a speaker identification reference pattern and a speaker identification verification pattern, generate a speaker identification reference pattern from the audio samples and a speaker identification verification pattern from other audio samples, compare the speaker identification verification pattern with the speaker identification reference pattern; and provide a response indicating whether the speaker identification verification pattern and the speaker identification reference pattern were generated based on audio samples from the same person. The system may be employed on a mobile phone in near field communication with a control system and may include a management platform.

Abstract: Hardware and/or software systems, devices, networks, and methods of the present invention enable increased levels of security and increase resistance to unauthorized access to secure systems by performing identity recognition and verification based on vocal spectrum analysis. Enrollment and verification processes enable a score to be ascribed to access attempts by person, provide spoof identification, and associate potential relatives of enrolled speakers. The present invention may be employed across a wide range of applications including voice login for mobile phone, tablets, laptops, etc., smartcards for various systems and devices, and software applications running on the devices.

Abstract: A distributed sensor network has a base station and clusters of sensor nodes. In a method of locating and classifying signal sources, at each node divides a received signal into blocks, performs Fourier-based transform on the blocks, selects peaks from the transformed blocks, selects subbands with features of interest based on the frequency of occurrence of the peaks across the blocks, collaborates with other nodes in the cluster to make a final selection of the subbands, encodes the subband features of the signal, and transmits the subband features to the base station. The base station processes the received subband features to locate and classify the signal sources.

Abstract: A system for determining the origin and trajectory of a gunshot includes spaced sensor nodes and a base station. A method for determining the origin and trajectory of a gunshot includes the steps of, at the nodes, sensing acoustic signals, converting the acoustic signals into digital signals, separating the digital signals into segments, calculating a time of arrival of each segment, and extracting features from each segment, and then at the base station identifying each time of arrival as a main shock wave or a main muzzle blast time of arrival from the features, and computing the trajectory from the main shock wave times of arrival. The computed trajectory includes velocity and acceleration. The method also includes computing, at the base station, the origin from the main muzzle blast times of arrival.

Abstract: A distributed sensor network has a base station and clusters of sensor nodes. In a method of locating and classifying signal sources, at each node divides a received signal into blocks, performs Fourier-based transform on the blocks, selects peaks from the transformed blocks, selects subbands with features of interest based on the frequency of occurrence of the peaks across the blocks, collaborates with other nodes in the cluster to make a final selection of the subbands, encodes the subband features of the signal, and transmits the subband features to the base station. The base station processes the received subband features to locate and classify the signal sources.