Sensay analyticstm: A real-time speaker-state platform

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 huma...

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Bibliographic Details
Main Authors: Tsiartas, A., Albright, C., Bassiou, N., Frandsen, M., Miller, I., Shriberg, E., Smith, J., Voss, L., Wagner, V.
Format: Conference Proceeding
Language:English
Subjects:
Acoustics
Affective computing
Computer architecture
emotion detection
Monitoring
Real-time systems
Robustness
social signalprocessing
speaker-state analysis
Speech
speech analytics
Online Access:Request full text
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Summary: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.
ISSN:2379-190X
DOI:10.1109/ICASSP.2017.8005306