- Environmental monitoring with uChipPosted 3 days ago
- ARDULEGO KIT: create with Lego and ArduinoPosted 3 weeks ago
- Share & Discover by PCBWayPosted 4 weeks ago
- ENERGY METER IOTPosted 4 weeks ago
- Energy Meter GSM with Arduino (part 2)Posted 1 month ago
- Energy Meter GSM with Arduino (part 1)Posted 2 months ago
- ARDULOCK: a keyboard with RFID modulePosted 2 months ago
- Autofocus Glasses/Phoropter Using Variable Focus Liquid LensPosted 4 months ago
- Home Automation & Lights controlling SystemPosted 4 months ago
- Solar TrackerPosted 4 months ago
Offline Speech Recognition on Raspberry Pi 4 with Respeaker
In this article we’re going to run and benchmark Mozilla’s DeepSpeech ASR (automatic speech recognition) engine on different platforms, such as Raspberry Pi 4(1 GB), Nvidia Jetson Nano, Windows PC and Linux PC.
2019, last year, was the year when Edge AI became mainstream. Multiple companies have released boards and chips for fast inference on the edge and a plethora of optimization frameworks and models have appeared. Up to date, in my articles and videos I mostly focused my attention on the use of machine learning for computer vision, but I was always interested in running deep learning based ASR project on an embedded device. The problem until recently was the lack of simple, fast and accurate engine for that task. When I was researching this topic about a year ago, the few choices for when you had to run ASR (not just hot-word detection, but large vocabulary transcription) on, say, Raspberry Pi 3 were:
-
CMUSphinx
-
Kaldi
-
Jasper
Buy Raspberry Pi from our store!