AI/ML

A/V de-sync detection

• Automatic a/v de-sync detection by using ML/AI algorithms.
• Detection algorithm is independent from the audio track language.
• Option for additional learning process for neural network.

Why teams choose Vroves A/V Desync Detection

Catch out-of-sync streams before your audience does. Audio-video desynchronization is one of the most common - and most frustrating - quality issues in broadcast, OTT and live streaming. The Vroves SDK finds it automatically at scale, so you can fix problems during ingest or QA instead of waiting for viewer complaints.

• Language-independent: works on any audio track - no per-language models to maintain
• Cross-platform C API: Linux, macOS and Windows; drop into your existing pipeline in days
• Docker deployment available: run it as a service alongside your media stack with zero native dependencies

Typical use cases

Broadcast and OTT QA pipelines: scan every ingest for sync drift before it reaches viewers. Live streaming monitoring: flag out-of-sync streams in real time so operators can intervene immediately.

Available on linux, mac and windows platforms. SDK contains of sample and easy to use C API. Available as a docker as well. Sensitive Scene Detector
Frame based scene analisys. In case of sensitive content there will be event triggered with frame num and time.
In work: automatic detection of the inappropriate content such as nudity, smoking, violence.

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