Speech Therapy Device Voice Control SDK
Speech therapy aid
How BotSurf works on a Speech Therapy Device
BotSurf runs on a Speech Therapy Device as an on-device AI voice agent, not a fixed list of matched commands. Voice exercises, feedback, progress tracking. Because the underlying engine is a real AI model rather than a command-matching layer, it handles phrasing variation, multi-step requests, and follow-up questions the way a person actually talks — not the rigid "say this exact phrase" pattern older voice integrations require.
The manufacturer opportunity
Therapy and education market. This is a genuine AI differentiator, not a rebadged wake-word matcher — Speech Therapy Device manufacturers can market real on-device AI reasoning, multi-step task handling, and privacy-preserving local processing, positioning against competitors still shipping fixed-command "voice control" as if it were the same thing.
Hardware & memory baseline
The floor Education & Learning devices need to clear before integration; exact figures are confirmed per project once we know your chipset and target markets.
Minimum RAM
2 GB for student tablets and classroom devices; 1 GB acceptable for single-purpose kiosks (library, museum)
Minimum storage
4 GB — the preloaded book/audiobook catalog and accessibility tooling (read-aloud, translation) need real headroom
CPU architecture
ARM Cortex-A55 or better, widely available in the education-tablet price band this category typically targets
Microphone array
Single mic sufficient for most classroom use; 2-mic arrays improve reliability in noisy classroom/library environments
Network
School Wi-Fi for research and live content; accessibility features (text-to-speech, offline-cached reading) work without connectivity
Content controls
Centralized, institution-set catalogs and permissions are standard for this category — a school decides what's reachable, not a fixed default
Chipset compatibility
Compatible with the budget-to-midrange ARM SoCs (MediaTek, Unisoc, entry Snapdragon) dominant in education-tablet hardware