How is it going? Less false positive?
Dear @geoffrey, you’re welcome!
Hopefully the instruction is understandable and without mistakes. While writing it together I have optimized a little bit, therefore there might be errors. Please let me know if something does not work.
Because of the documentation I tried Porcupine first, because there are some free wake words which can be used for an unlimited time. For this reason my Rhasspy listens to “hey pico” from the very beginning. But often the wake word was triggered unintentionally by background noise or conversations. If the detection rate is low, the wake word must be called several times - no solution for me.
Afterwards I tried Sonowboy, both with one (i.e. 3 sample files) and several attempts (I created numerous accounts, and spoke about 20 x 3 wake words into the model - that took as long as getting Precise to run). Still the same problem as with Porcupine. The cofiguration via the website is terrible, especially if you do several iterations of the training using numberous accounts.
Since Rhasspy always detects something (and does so very well when triggered intentionally), false positive reactions are undesirable. Especially if the smart home can already control some things. Therefore I have - sad as it is - deactivated the wake word detection via the api at the moment. Rhasspy currently only works as voice output based on automation, but does not listen. That is a pity!
So I tried Precise, even though - as mentioned above - it is not supported yet but will come in version 2.5. At the moment I can’t say anything about the real usage.
I only have information about the internal test - here you can test the wake word model against an own data set (30 GB wav) and get a false detection rate. This has improved after repeated training as the data set grew and now stands at 99.94%.
I’m waiting patiently for version 2.5 and am happy to check if this number withstands real conditions. As mentioned before: If problems occur, your work is not in vain. You can always add more files with your wake word using different tones / speeds / … or enlarge the data set with audio files that do not contain your wake word and improve quality by training again.
I give advance praise and claim: More data = better recognition.
What is interesting about this approach is that we could create hopefully really personalized wakewords. I experimented with custom Snowboy wakewords like e.g. Pollie, but that gave lots of false positives.
At the moment Snowboy is reasonably working well, although the kids think I’m shouting “cowboy” the entire day. Today our 4 year old was able to trigger Rhasspy and to turn on the kitchen cabinet lights on using the Dutch profile.
The parts I ordered for the Rhasspy satellite are arriving today, so that’s the first thing on the list to address and once that’s working, I’m considering placing one in the kids bedroom (deactivating wakeword detection when they are in bed using an automation 
)
If all that goes to plan, I’ll see if I can further look into Precise, hopefully finding relevant data sources. I assume you speak German, so if it works for you, then it should be feasible to do it in Dutch (Flemish) as well.
With children it is certainly quite exciting what is intentionally and unintentionally triggered. My parrots do not imitate human language - we communicate our emotions with each other through gestures and sounds (happy, interested, bored, hungry, …). Therefore it is easier for me to separate these sounds from human sounds in training (as compared to small children).
Funny: The satellite of Rhasspy is waiting in my drawer and waits, because my motto is: First a working system with a proper wake word (everything else works great) and then the satellites.
Some data on sounds will be useful for training, regardless of the language: white, brown, … noises and ambient sounds like vacuum cleaners etc. In addition, the English language is present in movies, series and music - you can use some of it here. For data in your own language you can use data from podcasts, news, TV shows. You only need a way to get mp3 or wav files.
It is important with this approach that the selected hot word is very unlikely to appear in the data set. My hotword “hey pico” will most likely not appear in the selected songs, German news broadcasts, …
I have added links to sources of data for data/random in my instructions given aboveand will extend these list of links, if I find or get mentioned further sources.
This whole topic gets now much more important as snowboy is wrapping up (as you can read here): https://github.com/Kitt-AI/snowboy and therefore should probably not even be an option for rhasspy anymore. I wonder how well mycroft.ai is doing with the current crisis.
@ulno: That sounds exciting!
I really hope that Precise’s performance is better as compared to snowboy as well as porcupine and that mycroft will survive the crisis.
I have already played with the pre-2.5 - but I can’t make Precise work yet.
wow, F!!! Snowboy works amazing on my part, no false positive !
Have you tried on 2.4.19? I think I had
“Hey Mycroft” running there for a short time - back to “porcupine” for the moment. What is going wrong for you on 2.4.19 with precise or just trouble on 2.5?
And did you see this? https://github.com/synesthesiam/rhasspy/issues/169
I had to apply that to make it work.
Hope, we can convince you to pitch in for some precise effort in the future 
Oha, I thought precise only worked from 2.5 on! 
Just tried it again with 2.4.19. Once I defined “system”: “precise”, rhasspy does not load the configuration anymore.
@ulno How does your configuration look like, when “Hey Mycroft” worked for you? 
EDIT: I don’t quite understand how precise could work for you. I can’t get Rhasspy 2.4.19 started with precise. The log is quite clear: ModuleNotFoundError: No module named ‘precise_runner’
@KiboOst:My condolences on the slow death of snowboy.
My config for the wakeword looks like this (precise does not work, porcupine and snowboy do work):
"wake": {
"system": "precise",
"precise": {
"model": "hey-mycroft-2.pb",
"sensitivity": "0.5",
"trigger_level": "3",
"chunk_size": "2048"
},
"porcupine": {
"keyword_path": "porcupine/hey_pico_raspberrypi.ppn",
"sensitivity": "0.65"
},
"snowboy": {
"audio_gain": "0.90",
"model": "snowboy/hey_pico/33_hey_pico_tone_mod_full_2x.pmdl",
"sensitivity": "0.6"
}
},
"rhasspy": {
"listen_on_start": true
}the runner error is the one you can fix here: https://github.com/synesthesiam/rhasspy/issues/169
Config looks fine. Try the runner fix. It’s pretty dirty to apply as you have to edit a mycroft precise file in your virtualenv - for me that was edit /home/pi/rhasspy/.venv/lib/python3.7/site-packages/precise_runner/runner.py:65
This was unfortunately predictable… They should open source everything. Alas it won’t happen…
Bye bye Snowboy…
The vocal assistant field is starting to become scarce (Snips, Snowboy, …).
Porcupine is only working correctly for English speakers… How long until Mycroft is bought or shuts down… at least Precise is fully open sourced and can be maintained even if Mycroft disappears.
I’d be very interested in Precise detection performance…
I think, we all should give mycroft precise some love and maybe see if we can even train as a community some more wakewords - I can offer help for training English, German, and Portuguese wakewords and also happy to push this for some more commercial applications outside the home automation environment (when I ever am allowed to return to university). Maybe, we could even push the mycroft community to re-implement some of rhasspy’s achievements back into their system- not sure if this is a political issue @synesthesiam? Sorry if I overstep here. For me rhasspy is so much easier to use than mycroft, but that might be personal - I think there should be at least mutual acknowledgement.
I am happy to let our community use my youtube tracks for noise or failure training (especially my lectures should have a lot of real background noise) - I bet there are some other youtubers around in this community or ones we know that we could ask?
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I guess I didn’t read consciously enough - you have already written it above. Excuse me!
@ulno EDIT:
I have not found a corresponding file in my docker container from Rhasspy. Your path is:
/home/pi/rhasspy/.venv/lib/python3.7/site-packages/precise_runner/runner.py:65
I searched Rhasspy for “precise_runner” and “site-packages”:
docker exec -it Rhasspy bash
find / -name "*site-packages*"
/usr/local/lib/python2.7/site-packages –> This path is empty.
find / -name "*precise_runner*"
No result!
So I set precise as wakeword again in the profile file, restarted Rhasspy to make sure that the current container has already tried to start with Precise. Again: No success, because no search result. A pity!
The code I want to fix is as follows:
return_time = 1e10 if timeout is None else ( timeout + time.time() )
Therefore I have set out on a search with the following order:
grep -iRls "return_time" ./
No result!
I don’t seem to have the runner.py
Not sure about docker - I despise docker and try to avoid it at all costs - it’s permission system is even worse than chroot and it’s an abolute nightmare to set up on windows and macos - but that is personal preference.
When you are in the docker, is there some kind of default python environment - you could just do a pip install mycroft-precise there - after that you should have precise (and maybe also the runner.py-file)
On a side note installing rhasspy in a virtual env is actually not that hard.
And reading your description again, did you actually search inside the docker image? You might have to start bash inside the docker and then search there.
This would be much appreciated 
I’d be happy to host the training data in the Rhasspy repos, unless you’d prefer to keep it separate. I’d also be willing to run training on my home server.
I have another project that’s been shelved for the time being, but may be relevant here. I’ve found and trained a number of MaryTTS voices, but I don’t have full coverage yet for all of Rhasspy’s supported languages. Perhaps we could launch something to help people donate voice samples for wake words or TTS voices?
No political issue, I just don’t have the extra time to reach back into the Mycroft community. Anyone is welcome to pull pieces of Rhasspy into whatever they’d like.
I haven’t looked into if there’s any way to interoperate with Mycroft. I do mention them in the documentation as the current best alternative if you’re cool with your voice being shipped over the internet to some server.
2 Likes
For me with semi-laymanlike Linux knowledge (I’m failing myself up) Docker has certain advantages through the container approach.
Thanks for the idea! I installed python, and then tried to install precise.
apt install python-pip
pip install mycroft-precise
Unfortunately, that doesn’t work as staed below. Maybe I just have to wait until Rhasspy 2.5 is finished forging.
Could not find a version that satisfies the requirement tensorflow<1.14,>=1.13 (from mycroft-precise) (from versions: )
No matching distribution found for tensorflow<1.14,>=1.13 (from mycroft-precise)just a guess:
is that python2 or 3?
Maybe give pip3 a chance?
Thanks for the hint! Using pip3 did not solve the problem.
sudo apt install python3 -pip
pip3 install mycroft-preciseSorry, the only help I can offer is now to support you in trying the virtual env instead of the docker.
However, I still don’t believe that the runner.py is nowhere in the docker.
Did you try sudo docker run -ti synesthesiam/rhasspy-server:latest bash and then search there? And also the pip3 stuff needs to run in there if you don’t find precise’ runner.py there.