Speech Analytics for Actionable Insights
Current Status, Recommendations, and Guidance
Speech analytics utilizes speech recognition, predictive analytics, and authentication of the data streams while assessing customers' complaints in real-time. Assessment occurs through the collection and analysis of current data mixed with historical facts to determine patterns and to predict trends. In the current research, the authors have chosen to focus primarily on speech analytics, serving as an umbrella term encompassing speech analytics, audio-mining technologies. The use of speech analytics typically refers to a broader range of speech products, such as analyzing voice identification, emotion detection, and phonetics/speech analysis. Speech Analytics for Actionable Insights proceeds with the discussion of an overview of enterprise needs for speech analytics, a brief history of the speech recognition, the infrastructure of phonetic versus transcription approaches and real-time versus post-call solutions, major speech analytics vendors and their features, applications found within case studies, and recommendations and guidance. The primary goal of this monograph is to help business decision-makers educate themselves on the burgeoning field of speech analytics as well as to understand how it impacts the broader enterprise landscape.
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Speech analytics utilizes speech recognition, predictive analytics, and authentication of the data streams while assessing customers' complaints in real-time. Assessment occurs through the collection and analysis of current data mixed with historical facts to determine patterns and to predict trends. In the current research, the authors have chosen to focus primarily on speech analytics, serving as an umbrella term encompassing speech analytics, audio-mining technologies. The use of speech analytics typically refers to a broader range of speech products, such as analyzing voice identification, emotion detection, and phonetics/speech analysis. Speech Analytics for Actionable Insights proceeds with the discussion of an overview of enterprise needs for speech analytics, a brief history of the speech recognition, the infrastructure of phonetic versus transcription approaches and real-time versus post-call solutions, major speech analytics vendors and their features, applications found within case studies, and recommendations and guidance. The primary goal of this monograph is to help business decision-makers educate themselves on the burgeoning field of speech analytics as well as to understand how it impacts the broader enterprise landscape.
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