Robust Speech Recognition in Embedded Systems and PC Applications

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Bibliographic Information

April 28, Roth; Daniel L. March 17, Roth; Daniel L. October 28, Roth; Daniel L. December 25, Roth; Daniel L.

About Jordan Cohen

May 29, Roth; Daniel L. Volume , Issue 2, pp.

As CTO of Voice Signal Developed and managed intellectual property program, including patent production, pursuit, litigation, and strategy, which created more than 40 patents in 3 years. Co-authored 13 granted patents, several more pending. DARPA funded, 30 researchers for 6 weeks. Program continues annually at Johns Hopkins.

Noise Robust Keyword Spotting Using Deep Neural Networks For Embedded Platforms

Developed Vocal Tract Length Normalization, now used in all major speech systems. While a staff member at IBM Developed the first successful auditory front end for a large scale speech recognition system. Created robust signal processing solutions for Audience to enhance Speech Recognition performance.

Resolved performance problems in Telenav speech processing systems. Advised and managed Automatic Speech Recognition portion of a potential multi-million dollar proposal for Basis Technologies.

Range of Services

Currently serving as Chief Scientist of Voice Morphing, a California start-up, and co-CTO of Kextil, engaged in voice-centric interfaces for the field service industry. Continuing with legal prior art and expert witness work for various customers in speech recognition and human interfaces, including successful defense against patent infringement in Nuance vs Vlingo in Boston, Created new business opportunities, including BALTIC, a virtual institute for language innovation which required negotiations with the staff of the House Armed Services Committee and various representatives.

Created new algorithms for machine translation. I have worked in different aspects of multimodal human-machine interaction for embedded systems. During my PhD thesis, I designed and built a computer interface that captures handwriting using a single camera. The user was allowed to write at will on a normal piece of paper with a common pen while, at the same time, the handwritten text was being captured. I further developed a personal identification system using signatures captured with the interface.

Robust Speech Recognition in Embedded Systems and PC Applications

The performance of the system was shown to be comparable to the best performances of camera-based identification systems present in the literature. Upon completion of my PhD, I joined VocalPoint Technologies, where I participated in the development of robust speech recognition algorithms for telephony.

After VocalPoint, I joined Evolution Robotics , a technology company focused on developing a software platform for robotics applications, where I have led the human-robot interaction group. A robot needs to interact directly with a noisy, dynamic, and unpredictable environment.

Thus, the design of the human-robot interaction is vital for creating an interesting and engaging relationship between humans and robots. At Evolution Robotics, I have developed human-robot interaction systems based on vision and speech. I have also worked on a novel interaction mode for the Sony AIBO robot that is based on a very efficient and robust visual pattern recognition system that was ported and optimized from a Pentium-class CPU to an embedded platform.

The area of visual pattern recognition and its application to visual simultaneous localization and mapping visual SLAM has been my primary focus lately.

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