8 ms·

DeepSpeech 60x Smaller, 9x faster, and 2x accuracy

75 points by kenarsa 5y ago

themerone 5y ago
Repo has Apache license, but is loaded with binary blobs and requires paid access keys.
spupe 5y ago
Title is very confusing. And there is no benchmark whatsoever to back up those claims.
- moffkalast 5y ago
  Well there's this: https://raw.githubusercontent.com/Picovoice/speech-to-text-benchmark/master/res/summary.png https://raw.githubusercontent.com/Picovoice/speech-to-text-b... So allegedly twice as accurate as Google Assistant, which sounds very impressive. No clue if it would run in real time on something like a Jetson Nano though.
  - kenarsa 5y ago
    Clarification. Google STT has to services. standard and enhanced. we are just better than enhanced and much better than standard. enhanced is much pricier than standard if you wonder what the diff is. It runs real-time on NVIDIA Jetson Nano and RPI 3/4. If you think we should consider other embedded platforms we love to hear what and why
    - moffkalast 5y ago
      > and RPI 3/4 Woah, now that is cool. Are you guys considering a Mycroft integration at some point?
      - kenarsa 5y ago
        mycroft already integrated our wake word (porcupine). we remain neutral and anyone can use our tech :)
colechristensen 5y ago
What are the state of the art open solutions to local voice recognition? Preferably with available models that a small org can also train themselves without millions in hardware.
- albertzeyer 5y ago
  Kaldi, K2, ESPNet.
  - misc1234 5y ago
    Nemo
- rileyphone 5y ago
  I will add https://github.com/coqui-ai/STT https://github.com/coqui-ai/STT, which is a continuation of DeepSpeech. Also, I've been messing around with https://github.com/ideasman42/nerd-dictation https://github.com/ideasman42/nerd-dictation, which works on a VOSK backend - accuracy is decent, especially with the bigger model.
- trowngon 5y ago
  Vosk https://github.com/alphacep/vosk-api https://github.com/alphacep/vosk-api
rhacker 5y ago
Title should be adjusted to: Picovoice/leopard: On-device speech-to-text engine powered by deep learning Since the claim is only in the HN title and not in the actually page that is linked.
- froh 5y ago
  Some benchmarks are here: https://github.com/Picovoice/speech-to-text-benchmark#results https://github.com/Picovoice/speech-to-text-benchmark#result... That is however not the linked page indeed.
  - kenarsa 5y ago
    Thank you for the clarification. `[1]` and `[2]` hyperlinks in the intro section point the benchmark
    - posguy 5y ago
      The Mozilla DeepSpeech tests on LibreSpeech listed in OPs link were out of date back in 2020[1], and Coqui.ai (the continuation of Mozilla DeepSpeech) isn't even benchmarked. Additionally, where is the comparison to Vosk and the other noteworthy platforms? How old is the data for IBM, Azure, Amazon and Google? https://github.com/Picovoice/speech-to-text-benchmark/issues/7 https://github.com/Picovoice/speech-to-text-benchmark/issues...
      - kenarsa 5y ago
        The benchmark is using the latest stable of DS >>> https://github.com/Picovoice/speech-to-text-benchmark/blob/master/requirements.txt#L3 https://github.com/Picovoice/speech-to-text-benchmark/blob/m... the data for cloud-based is from 2022.
  - deleted 5y ago
    [deleted]
wantsanagent 5y ago
Is this OSS? It looks like it has licenses and account limits baked in. Or is the release under Apache a green light to strip all that out?
- simcop2387 5y ago
  Can't confirm but based on their site, I suspect that the code is OSS, but the model isn't. And that license to get the model from them is what you're getting. Not sure how they enforce or deal with the number of hours transcribed though because they say they don't collect data and the whole thing happens on device.
  - jka 5y ago
    It would be great to have industry-recognized, concise terms for this kind of situation ("project is (FL)OSS, but contains proprietary machine learning"). For deployment of services we have "self-hosted", "cloud" and "on-prem", for example. For ML-based projects could we have something like "teachable" (as in you can "raise" the model the way you would like to) vs "pre-directed"? (it's been a long day; these probably aren't the neatest suggestions)
- themerone 5y ago
  Definately not. The repo is full of precompiled dlls.
pumanoir 5y ago
Is there anything as accurate and as small but Open Source and no subscriptions? Or at least just a small tflite model with similar specs?
jijji 5y ago
it says its on device, but then mention its $899/month
gigel82 5y ago
> You would need internet connectivity to validate your AccessKey with Picovoice license servers even though the voice recognition is running 100% offline. Plus closed source binaries checked into GitHub which is always a red flag; you're basically using it for free distribution of your paid software.
kneel 5y ago
Paid software on github, this post is just an ad.
rileyphone 5y ago
steps to try it out: - sign up for an account to get an access key - install demos with `npm install -g @picovoice/leopard-node-demo` - run `leopard-mic-demo -a $ACCESS_KEY` I'm pretty impressed with the accuracy, especially given it's all local and a 20MB model (though the total weight with node modules included comes out to 36MB). Obviously the licensing restrictions are a bummer, but 100 hours a month should be more than enough for my purposes - I like to compose thoughts with my voice sometimes and capture something as close to the stream of consciousness as possible. Really curious to see what gets built on this.
FloatArtifact 5y ago
Accuracy is important but latency plays an important role for viable speech recognition.

75 points by kenarsa 5y ago

themerone 5y ago

Repo has Apache license, but is loaded with binary blobs and requires paid access keys.

spupe 5y ago

Title is very confusing. And there is no benchmark whatsoever to back up those claims.

moffkalast 5y ago
Well there's this: https://raw.githubusercontent.com/Picovoice/speech-to-text-benchmark/master/res/summary.png https://raw.githubusercontent.com/Picovoice/speech-to-text-b... So allegedly twice as accurate as Google Assistant, which sounds very impressive. No clue if it would run in real time on something like a Jetson Nano though.
- kenarsa 5y ago
  Clarification. Google STT has to services. standard and enhanced. we are just better than enhanced and much better than standard. enhanced is much pricier than standard if you wonder what the diff is. It runs real-time on NVIDIA Jetson Nano and RPI 3/4. If you think we should consider other embedded platforms we love to hear what and why
  - moffkalast 5y ago
    > and RPI 3/4 Woah, now that is cool. Are you guys considering a Mycroft integration at some point?
    - kenarsa 5y ago
      mycroft already integrated our wake word (porcupine). we remain neutral and anyone can use our tech :)

colechristensen 5y ago

What are the state of the art open solutions to local voice recognition? Preferably with available models that a small org can also train themselves without millions in hardware.

albertzeyer 5y ago
Kaldi, K2, ESPNet.
- misc1234 5y ago
  Nemo
rileyphone 5y ago
I will add https://github.com/coqui-ai/STT https://github.com/coqui-ai/STT, which is a continuation of DeepSpeech. Also, I've been messing around with https://github.com/ideasman42/nerd-dictation https://github.com/ideasman42/nerd-dictation, which works on a VOSK backend - accuracy is decent, especially with the bigger model.
trowngon 5y ago
Vosk https://github.com/alphacep/vosk-api https://github.com/alphacep/vosk-api

rhacker 5y ago

Title should be adjusted to: Picovoice/leopard: On-device speech-to-text engine powered by deep learning Since the claim is only in the HN title and not in the actually page that is linked.

froh 5y ago
Some benchmarks are here: https://github.com/Picovoice/speech-to-text-benchmark#results https://github.com/Picovoice/speech-to-text-benchmark#result... That is however not the linked page indeed.
- kenarsa 5y ago
  Thank you for the clarification. `[1]` and `[2]` hyperlinks in the intro section point the benchmark
  - posguy 5y ago
    The Mozilla DeepSpeech tests on LibreSpeech listed in OPs link were out of date back in 2020[1], and Coqui.ai (the continuation of Mozilla DeepSpeech) isn't even benchmarked. Additionally, where is the comparison to Vosk and the other noteworthy platforms? How old is the data for IBM, Azure, Amazon and Google? https://github.com/Picovoice/speech-to-text-benchmark/issues/7 https://github.com/Picovoice/speech-to-text-benchmark/issues...
    - kenarsa 5y ago
      The benchmark is using the latest stable of DS >>> https://github.com/Picovoice/speech-to-text-benchmark/blob/master/requirements.txt#L3 https://github.com/Picovoice/speech-to-text-benchmark/blob/m... the data for cloud-based is from 2022.
- deleted 5y ago
  [deleted]

wantsanagent 5y ago

Is this OSS? It looks like it has licenses and account limits baked in. Or is the release under Apache a green light to strip all that out?

simcop2387 5y ago
Can't confirm but based on their site, I suspect that the code is OSS, but the model isn't. And that license to get the model from them is what you're getting. Not sure how they enforce or deal with the number of hours transcribed though because they say they don't collect data and the whole thing happens on device.
- jka 5y ago
  It would be great to have industry-recognized, concise terms for this kind of situation ("project is (FL)OSS, but contains proprietary machine learning"). For deployment of services we have "self-hosted", "cloud" and "on-prem", for example. For ML-based projects could we have something like "teachable" (as in you can "raise" the model the way you would like to) vs "pre-directed"? (it's been a long day; these probably aren't the neatest suggestions)
themerone 5y ago
Definately not. The repo is full of precompiled dlls.

pumanoir 5y ago

Is there anything as accurate and as small but Open Source and no subscriptions? Or at least just a small tflite model with similar specs?

jijji 5y ago

it says its on device, but then mention its $899/month

gigel82 5y ago

> You would need internet connectivity to validate your AccessKey with Picovoice license servers even though the voice recognition is running 100% offline. Plus closed source binaries checked into GitHub which is always a red flag; you're basically using it for free distribution of your paid software.

kneel 5y ago

Paid software on github, this post is just an ad.

rileyphone 5y ago

steps to try it out: - sign up for an account to get an access key - install demos with `npm install -g @picovoice/leopard-node-demo` - run `leopard-mic-demo -a $ACCESS_KEY` I'm pretty impressed with the accuracy, especially given it's all local and a 20MB model (though the total weight with node modules included comes out to 36MB). Obviously the licensing restrictions are a bummer, but 100 hours a month should be more than enough for my purposes - I like to compose thoughts with my voice sometimes and capture something as close to the stream of consciousness as possible. Really curious to see what gets built on this.

FloatArtifact 5y ago

Accuracy is important but latency plays an important role for viable speech recognition.