Real-time speech analytics: Building live dashboards on your voice API stack

Real-time speech analytics involves building live dashboards on a voice API stack by navigating through five main stages: capture, transport, streaming automatic speech recognition (ASR), intelligence, and user interface (UI) push. Each of these stages independently contributes to latency and cost, which are critical factors in ensuring the effectiveness of the dashboard in a production environment. The decision to build or buy the analytics layer is influenced by the need for control, speed of rollout, and embedding requirements, with compliance considerations such as HIPAA playing a crucial role. The article discusses how selective activation of intelligence features can help control costs in per-feature pricing models, and emphasizes the importance of compliance with regulations like HIPAA when dealing with electronic Protected Health Information (ePHI). It also explores the benefits of a hybrid approach that balances building and buying, and provides guidance on starting the development of a live dashboard with streaming transcription, interim results, and the integration of intelligence features like Sentiment Analysis.

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