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Complex deep learning models run quickly and efficiently for speech recognition.
Memory footprint of a microwave language model reduced from 17 MB to 1.6 MB.
Customizable, accurate speech recognition, while adhering to consumer devices constraints.
Discover the Real-World Impact of Edge AI
Explore in-depth use cases that show how edge AI is powering the next generation of IoT, solving real-world problems, driving faster decisions, and lowering costs through smarter operations right at the device level.
KEY TAKEAWAYS
- Sensory delivers embedded voice assistants using Arm-based processors for offline, private control.
- Arm Cortex-M55 and Ethos-U55 powered speech models with no need for cloud connectivity.
- Arm quantization and Helium optimizations reduced model size from 17 MB to 1.6 MB.
- Sensory used Arm tools to partition workloads and improve speed, power, and responsiveness.
- Arm enabled Sensory to deliver fast, private voice control within microcontroller constraints.