Blog

Nine ready-to-deploy offline sound recognition models, one C SDK: the model matrix with each model's value and IPC/vertical use, the shared recognition pipeline, HiSilicon and Ingenic NPU adaptation, and the path from evaluation to deployment.

From the fundamental-formant signature of crying and the full recognition pipeline to baby monitors, smart cameras and in-car CPD — with benchmark data and device-side performance.

Time- and frequency-domain traits of snoring (2–4 s rhythm, 80–120 Hz fundamental), event-based detection, sleep-report products and anti-snore intervention.

Burst-series verification across dog breeds, graded alerts for doorbells and outdoor cameras, and how to keep bark-like speech and traffic from triggering false alarms.

The underrated meow-vs-cry discrimination problem, alone-time care workflows, and how long-term vocal data becomes a behavior health record for cats.

The two-stage impact-and-shatter signature, deployment positions and calibration, and chain-store night security.

Smoke, CO and car alarms each carry a distinctive pattern; class recognition drives graded notification — and turns into a hearing layer for elderly care.

The millisecond transient fingerprint and echo evidence, city-scale deployment (survey, calibration, four-layer architecture), and campus/commercial-district guard workflows.

Pulse-group verification against footsteps and door slams, doorbell and smart-lock applications, and the graded design that turns knocking into a call for help in elderly care.

Sustained-pitch evidence against singing and cheering, solo-living contact chains, and the night-time public-space safety net.