https://rhasspy.readthedocs.io Haven't used it, but seems very nice. https://youtu.be/ijKTR_GqWwA
It can use https://github.com/cmusphinx/pocketsphinx (offline) or Kaldi(offline), or Google(online) for the "speech-to-text"-part.
Ask HN: Non-cloud voice recognition for home use?
61–70 of 130 posts
Re: Ask HN: Non-cloud voice recognition for home use?
#62Earlier quoted context omitted.
Looks interesting. I've got a few GPUs I could use if the CPU is too much of a bottleneck. We've identified a dictionary of the types of commands and words we use and have a recording of all our amazon and other commands. Training wave files are not an issue. Have you had any issues with recognising multiple languages? Thanks!
Are you talking about recognizing multiple languages at once (e.g. you don't know which language the user will speak and you want it to react appropriately to all of them)? You're going to have a harder time doing that with any system, but it is possible. You would likely need to run multiple models and pick between their output, or train a specialized separate model that can classify the language, then use it to pic…
I'd expected some training required for each separately so we've got a decent collection of voice examples. Some of us mix languages within a sentence but that's a bad habit anyway so unsupported. I don't see figuring out the language as being a problem as my proof-of-concept already handles that well enough with around 90% accuracy. Once its selected a language then the appropriate model can be used. To make it fast we'd likely just keep the whole thing in RAM. Might need more however.
The issue I see with talon is its currently mac only. That would however still help one of us who lives on wheels (got a 16" macbook IIRC and a mac mini as well). Different set of use-cases so things would be more relaxed.
I see some hints about a linux version however. I've got windows / linux VMs on the server but no other macs. GPUs will be installed soon when I decom some old gaming rigs.
Plenty to think about.
Re: Ask HN: Non-cloud voice recognition for home use?
#63Earlier quoted context omitted.
Looks interesting. I've got a few GPUs I could use if the CPU is too much of a bottleneck. We've identified a dictionary of the types of commands and words we use and have a recording of all our amazon and other commands. Training wave files are not an issue. Have you had any issues with recognising multiple languages? Thanks!
My "workaround" for using offline recognition in several languages in `snips.ai` was configuring a different wake-word per language, and then running several wake-word-detectors on the same microphone input.
Exactly how mine works. Each language uses a different trigger. Simple.
Even then it can misinterpret so plenty of room for improvement. My quick POC is around 90% accurate for language detection based on the trigger word.
Re: Ask HN: Non-cloud voice recognition for home use?
#64Earlier quoted context omitted.
Are you talking about recognizing multiple languages at once (e.g. you don't know which language the user will speak and you want it to react appropriately to all of them)? You're going to have a harder time doing that with any system, but it is possible. You would likely need to run multiple models and pick between their output, or train a specialized separate model that can classify the language, then use it to pic…
I'd expected some training required for each separately so we've got a decent collection of voice examples. Some of us mix languages within a sentence but that's a bad habit anyway so unsupported. I don't see figuring out the language as being a problem as my proof-of-concept already handles that well enough with around 90% accuracy. Once its selected a language then the appropriate model can be used. To make it fast…
The talon beta is on windows/linux/mac. I was recommending wav2letter directly instead of talon specifically because you mentioned thin clients, and I'm not really targeting something like headless raspberry pis yet.
I mostly mentioned wav2letter@anywhere because it could handle a bunch of audio streams centrally, so you can stream from 16 pis to a central box, and it's very accurate.
Re: Ask HN: Non-cloud voice recognition for home use?
#65Disclaimer: I am the founder of Hiome, a smart home startup focused on private by design local-only products.
What actions are you looking to handle with the assistant?
Reason I ask is because a voice assistant is a command line interface with no auto-complete or visual feedback. It doesn’t scale well as you add more devices or commands to your home, because it becomes impossible to remember all the phrases you programmed. We’ve found the person who sets up the voice assistant will use it for simple tasks like “turn off all lights” but nobody else benefits and it gets little use beyond timers and music. They are certainly nice to have, but they don’t significantly improve the smart home experience.
If you’re looking to control individual devices, I suggest taking a look at actual occupancy sensors like Hiome (https://hiome.com), which can let you automate your home with zero interaction so it just works for everyone without learning anything (like in a sci-fi movie). Even if you’re the only user, it’s much nicer to never think about your devices again.
Happy to answer any questions about Hiome or what we’ve learned helping people with smart homes in general! -> neil@hiome.com
Re: Ask HN: Non-cloud voice recognition for home use?
#66https://rhasspy.readthedocs.io Haven't used it, but seems very nice. https://youtu.be/ijKTR_GqWwA
Rhasspy author here in case you have any questions :)
If you're looking for something for the command-line, check out https://voice2json.org
Re: Ask HN: Non-cloud voice recognition for home use?
#67Mozilla DeepSpeech trained on the Common Voice dataset for English. You can get pretrained models too. They have a nice matrix channel where you can get help, and pretty good documentation. It is also actively developed by several engineers. http://voice.mozilla.org/en/datasets and http://github.com/mozilla/DeepSpeech/
The models (`deepspeech-0.6.1-models.tar.gz`) weigh 1.14 gb, if anyone's interested.
Re: Ask HN: Non-cloud voice recognition for home use?
#68My company develops SDKs for on-device speech recognition on Android/iOS: https://keenresearch.com/keenasr-docs (Raspberry Pi is an option too, we'll have a GA release in Q2) We license this on commercial bases but would be open to indy-developer friendly licensing. We offer a trial SDK that makes testing/evaluation super easy (it works for 15min at the time). Ogi ogi@keeenresearch.com
> Currently, the SDK supports English and Spanish out of the box. Additional ASR Bundles for most major spoken languages can be provided upon request within 6-8 weeks. Does this mean you have a standing offer to train a new language on demand?
Yes, for a number of European and some Asian languages we can do this; it's mainly the question of business opportunity.
Re: Ask HN: Non-cloud voice recognition for home use?
#69You are welcome to try Vosk
https://github.com/alphacep/vosk-api
Advantages are:
1) Supports 7 languages - English, German, French, Spanish, Portuguese, Chinese, Russian
2) Works offline even on lightweight devices - Raspberry Pi, Android, iOS
3) Install it with simple `pip install vosk`
4) Model size per language is just 50Mb
5) Provides streaming API for the best user experience (unlike popular speech-recognition python package)
6) There are APIs for different languages too - java/csharp etc.
7) Allows quick reconfiguration of vocabulary for best accuracy.
8) Supports speaker identification beside simple speech recognition
Re: Ask HN: Non-cloud voice recognition for home use?
#70You are welcome to try Vosk https://github.com/alphacep/vosk-api Advantages are: 1) Supports 7 languages - English, German, French, Spanish, Portuguese, Chinese, Russian 2) Works offline even on lightweight devices - Raspberry Pi, Android, iOS 3) Install it with simple `pip install vosk` 4) Model size per language is just 50Mb 5) Provides streaming API for the best user experience (unlike popular speech-recognition p…
Sound great, thanks