What crucial limitation did early keyword spotting systems (c. 2001–2002) possess regarding conversational context?
Answer
They could tell what was said, but not how it was said or why the customer reacted
Systems built around keyword spotting logic—essentially 'if X then Y' rules applied to transcribed text—were effective for compliance checks or simple data flagging, but they suffered from a fundamental limitation in understanding context. They were excellent at identifying *what* specific words were uttered (e.g., 'refund policy'), but they possessed no mechanism to analyze the delivery or the surrounding emotional state. Consequently, they could not discern if the customer was highly agitated, satisfied, or merely resigned while mentioning that policy, meaning they measured adherence to script but not the quality of the customer experience.
Related Questions
What specific capability defined the achievement of Bell Labs' 'Audrey' system in the early 1950s?What distinction does IBM's Shoebox machine, developed around 1962, hold in the early timeline?What technological architecture crystallized in the 1980s underpinning modern ASR systems?What technological barrier, involving speech flow, had to be overcome before speech became a truly useful data source for large-scale analysis?Approximately when did the specific application known as speech analytics emerge in commercial contact centers?What was the first practical application of speech analytics deployed in contact centers?What crucial limitation did early keyword spotting systems (c. 2001–2002) possess regarding conversational context?What integration truly defined the major evolution of speech analytics beyond simple transcription tagging?According to research development, what is required to differentiate paralinguistic features from linguistic features in speech analysis?What early academic gathering in 1961 directed subsequent research efforts in speech recognition?