Computer Scientist, Speech Technology and Research Laboratory
Allen Stauffer’s main focus is preparing speech processing technologies for commercial and government transition, including software and hardware testing and validation, system evaluation and preparation of relevant data to meet client needs. A second facet of his work is in developing speech processing system requirements based on his understanding of client needs and interactions with the operational community.
He is currently focused on the DARPA Robust Automatic Transcription of Speech–Transition (RATS) program, where he is developing software development and testing processes designed to meet the requirements of a large number of operational use cases. As part of this effort he is actively involved in fielding systems, leading demonstrations of SRI technology and providing effective feedback and guidance on technology gaps and strengths.
Stauffer began work in the Audio Processing Group at the Air Force Research Laboratory (AFRL) in 2006 as an intern. He later joined the group full time in 2010 after completing his studies. His main focus at AFRL was in testing and evaluation of speaker and language recognition systems, and designing software development processes and Application Programming Interfaces (APIs) for speech systems.
Stauffer received his bachelor of science degree in computer science from Clarkson University in 2010. He went on to complete a master’s degree in computer science from the University of Texas at Dallas in 2014 with a focus on intelligent systems. His thesis dealt with the detection and mitigation of clipping in speech processing systems.
Recent publications
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Robust Speaker Recognition from Distant Speech under Real Reverberant Environments Using Speaker Embeddings
This article focuses on speaker recognition using speech acquired using a single distant or far-field microphone in an indoors environment.
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Voices Obscured in Complex Environmental Settings (VOiCES) corpus
This work is a multi-organizational effort led by SRI International and Lab41 with the intent to push forward state-of-the-art distant microphone approaches in signal processing and speech recognition.