I tried to use Pocketsphinx on ev3dev on Lego EV3 brick. I made and installed libraries sphinxbase-5prealpha and pocketsphinx-5prealpha as written there - http://cmusphinx.sourceforge.net/wiki/tutorialpocketsphinx. But a test fails: when I run "pocketsphinx_continuous -inmic yes", the program freezes on "INFO: ngram_search_fwdtree.c(186): Creating search channels" and then after about 30 minutes arrears "Killed". What is wrong?
I use a mic from a USB-webcam. The microphone works fine. I know this because I record a sound successfully.
64Mb of memory is not enough to run pocketsphinx continuous speech recognition. You can only use pocketsphinx for few commands with very simple model, not with a large vocabulary.
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Collect the data for your specific commands (1-5 hours is recommended in tutorial). Train an acoustic model based on tutorial, use it with a small grammar. Overall it is not easy to fit recognizer on such a limited hardware, you'd better figure out more powerful robot.
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I tried to use Pocketsphinx on ev3dev on Lego EV3 brick. I made and installed libraries sphinxbase-5prealpha and pocketsphinx-5prealpha as written there - http://cmusphinx.sourceforge.net/wiki/tutorialpocketsphinx. But a test fails: when I run "pocketsphinx_continuous -inmic yes", the program freezes on "INFO: ngram_search_fwdtree.c(186): Creating search channels" and then after about 30 minutes arrears "Killed". What is wrong?
I use a mic from a USB-webcam. The microphone works fine. I know this because I record a sound successfully.
64Mb of memory is not enough to run pocketsphinx continuous speech recognition. You can only use pocketsphinx for few commands with very simple model, not with a large vocabulary.
Thanks. Actually I want to use only 5-7 words to control EV3. How to start working with a simple model if I am using Python?
Collect the data for your specific commands (1-5 hours is recommended in tutorial). Train an acoustic model based on tutorial, use it with a small grammar. Overall it is not easy to fit recognizer on such a limited hardware, you'd better figure out more powerful robot.
Thanks for the theory but how to do it practically. Which apps do I need to use? Which commands?