Spontaneous Text-independent Audio Clustering Software

To address the Navy"s need for a system that can autonomously cluster a large database of audio files by speaker, Physical Optics Corporation (POC) proposes to develop a new Spontaneous Text-independent Audio Clustering Software (STACS) system. This proposed technology is based on a unique combination of sophisticated signal processing algorithms that performs analysis and identification of voice data within audio files. The innovation in providing a dual-transform architecture will enable STACS to perform robust speaker identification as the basis for clustering files. Files that produce audio characteristics similar to each other are considered to contain speech data from the same speaker. Conversely, files with dissimilar characteristics are deemed to contain data from different speakers and are therefore not clustered together. As a result, this technology offers excellent identification accuracy and strong noise immunity without the need for training data, which directly address the PM Intel requirements. In Phase I, POC will demonstrate the feasibility of STACS by processing data files associated with multiple speakers, quantifying the computational latency, and verifying the clustering accuracy. In Phase II, POC plans to enhance STACS to accommodate all standard codec and container file formats used in modern cellular telephony.