Redefining Voice Signal Processing with Habana Gaudi
Voice signal processing stands pivotal in AI’s progression, necessitating dynamic computational solutions. Enter Habana Gaudi: a paradigm in AI processors promising unparalleled efficiency and scalability. With voice signals’ intricate time-frequency dynamics, Gaudi’s integration with HBM2 offers optimized memory access while its support for TensorFlow and PyTorch bridges hardware power with software finesse. Emphasizing scalability, rapid memory access, and performance efficiency, Gaudi’s architecture is primed for next-gen voice applications, from generative models to emotion detection. This talk converges the innovative spirit of software engineers with the architectural prowess of Gaudi, heralding a transformative era in voice technology.
Speaker(s)
Rita Singh - Carnegie Mellon University/Associate Research Professor
Dr. Rita Singh is an Associate Research Professor at CMU’s Language Technologies Institute, where she leads the Center for Voice Intelligence and Security. She also co-leads the research groups on Robust Speech Processing, and Machine Learning for Signal Processing. With over 20 years in speech and audio processing, her recent focus has been on voice-based human profiling, blending AI and Voice Forensics. Her team has pioneered several world-firsts. In 2018, they created the first live voice profiling system, demonstrated live at the World Economic Forum. In 2019, they recreated Rembrandt’s voice from his facial self-portraits. In 2020, they pioneered the technology behind voice-driven Covid detection. She is the author of the book “Profiling Humans from their Voice,” and assists multiple federal and global agencies in forensic voice profiling. Her work has gained extensive global media coverage.
