A. Tsiartas, C. Albright, N. Bassiou, M. Frandsen, I. Miller, E. Shriberg, J. Smith, L. Voss, V. Wagner, “SenSay Analytics™: A real-time speaker-state platform,” in Proc. ICASSP 2017, March 2017.
Abstract
Growth in voice-based applications and personalized systems has led to increasing demand for speech- analytics technologies that estimate the state of a speaker from speech. Such systems support a wide range of applications, from more traditional call-center monitoring, to health monitoring, to human-robot interactions, and more. To work seamlessly in real-world contexts, such systems must meet certain requirements, including for speed, customizability, ease of use, robustness, and live integration of both acoustic and lexical cues. This demo introduces SenSay AnalyticsTM, a platform that performs real-time speaker-state classification from spoken audio. SenSay is easily configured and is customizable to new domains, while its underlying architecture offers extensibility and scalability.
