Sensay Analytics (Tm): A Real-Time Speaker-State Platform

A. Tsiartas, C. Albright,N. Bassiou,M. Frandsen, I. Miller,E. Shriberg,J. Smith, L. Voss, V. Wagner

ICASSP(2017)

引用 25|浏览147
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摘要
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.
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关键词
speech analytics,emotion detection,speaker-state analysis,affective computing,social signal processing
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