Published: 05 March 2024
Audio analytics enables applications to discern a person’s status or their surroundings. Combined with AI, this enables a richer, context-aware experience, or interface. Product leaders must assess their audio analytical capabilities, evaluate sound library partners and new generative AI techniques.
More sophisticated integration between sound sensors and AI techniques is driving the use of audio analysis beyond existing speech analytics.
The complexity of collecting comprehensive and quality sound databases remains a challenge, limiting the availability of large, consistent quality sound datasets. Emerging audio generative artificial intelligence (GenAI) models are increasingly used to cope with this complexity.
Audio analytics research and adoption centers on four use cases — context and scene analysis (smart cities, smart spaces); user status understanding (emotion, authentication); preventive and predictive maintenance (industrial); and preventive and diagnostic (health, medical).
To leverage the impact of emerging technologies and trends on
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