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Doing offline voice recognition is pretty challenging on Raspberry Pi since it is relatively underpowered. Using pocketSphinx with RPi 3, it takes 2-3x realtime
by xigency 7y ago
Doing offline voice recognition is pretty challenging on Raspberry Pi since it is relatively underpowered. Using pocketSphinx with RPi 3, it takes 2-3x realtime to do recognition, and the accuracy is underwhelming. Most DIY voice assistants handle voice recognition and speech synthesis with online services, defeating the privacy purpose.
If you would like to really take on Siri and Alexa, I would recommend using beefier hardware.
- perfmode 7y agoanyone aware of low-power ASICs available to DIY to perform inference using pre-trained models?
- dodobirdlord 7y agoYup, Google's Coral and NVIDIA's Jetson Nano. https://coral.withgoogle.com/products/ https://coral.withgoogle.com/products/ https://developer.nvidia.com/embedded/jetson-nano-developer-kit?nvid=nv-int-mn-78462 https://developer.nvidia.com/embedded/jetson-nano-developer-...
- Havoc 7y agoDon't think you need that much power for inference. Plus at siri levels you can probably push it to cloud if need be
- Havoc 7y ago>Doing offline voice recognition is pretty challenging on Raspberry Pi Mycroft is hooked into some sort of mozilla cloud thing (deepspeech) I gather. So plan is to roll a baseline and then see if I can local host a deep speech server >I would recommend using beefier hardware Plan is to ultimately deploy a gpu accelerated tensorflow integration so beefiness of hardware has been considered. >RPi 3 4 cause true gigabit and usb 3