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Sensay analyticstm: A real-time speaker-state platform

Andreas Tsiartas, Cory Albright, Nikoletta Bassiou, M. Frandsen, Ivan W. Miller, E. Shriberg, Jennifer Smith, Luke Voss, Valerie Wagner

发表年份
2017
引用次数
5

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.

关键词

Computer scienceScalabilityRobustness (evolution)ExtensibilityAnalyticsArchitectureSpeaker recognitionSpeech processingState (computer science)Human–computer interaction

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