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kenarsa

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投稿

On-Device Real-Time Speech-to-Speech Translation [video]

youtube.com
1 ポイント·投稿者 kenarsa·2 か月前·0 コメント

[untitled]

1 ポイント·投稿者 kenarsa·2 年前·0 コメント

Animating Ptolemy's Equant with Python, SVG, and CSS

rhodesmill.org
68 ポイント·投稿者 kenarsa·2 年前·5 コメント

Is there a library for creating SVG animations with Python?

1 ポイント·投稿者 kenarsa·2 年前·0 コメント

Compute-intensive cross-platform library, which language?

2 ポイント·投稿者 kenarsa·2 年前·2 コメント

How to do multiprocessing (NOT multithreading) on iOS?

1 ポイント·投稿者 kenarsa·2 年前·1 コメント

The importance of initialization and momentum in deep learning [pdf]

cs.toronto.edu
1 ポイント·投稿者 kenarsa·2 年前·1 コメント

Why MSVC still doesn't support C99 features like variable-length array (VLA)?

5 ポイント·投稿者 kenarsa·2 年前·1 コメント

Why is WebAssembly not supporting 256/512 SIMD registers?

1 ポイント·投稿者 kenarsa·2 年前·4 コメント

[untitled]

1 ポイント·投稿者 kenarsa·2 年前·0 コメント

Offline Voice Assistant on a Microcontroller with 192KB RAM

picovoice.ai
92 ポイント·投稿者 kenarsa·4 年前·31 コメント

Arduino Voice Recognition in 10 Minutes or Less

picovoice.ai
3 ポイント·投稿者 kenarsa·4 年前·0 コメント

[untitled]

1 ポイント·投稿者 kenarsa·4 年前·0 コメント

[untitled]

1 ポイント·投稿者 kenarsa·4 年前·0 コメント

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

github.com
75 ポイント·投稿者 kenarsa·4 年前·26 コメント

20MB is all you need for speech recognition

medium.com
3 ポイント·投稿者 kenarsa·4 年前·1 コメント

20MB is all you need for speech-to-text

medium.com
5 ポイント·投稿者 kenarsa·4 年前·0 コメント

Octopus: Google Search for Voice

github.com
1 ポイント·投稿者 kenarsa·5 年前·0 コメント

OctoTube: Voice Search for YouTube

medium.com
1 ポイント·投稿者 kenarsa·5 年前·0 コメント

Yet Another Voice Activity Detection Engine

medium.com
4 ポイント·投稿者 kenarsa·5 年前·0 コメント

コメント

kenarsa
·11 か月前·議論
[flagged]
kenarsa
·11 か月前·議論
[flagged]
kenarsa
·11 か月前·議論
[flagged]
kenarsa
·11 か月前·議論
Try https://github.com/Picovoice/orca
kenarsa
·2 年前·議論
GitHub: https://github.com/Picovoice/picollm Platform: https://picovoice.ai/blog/picollm-local-llm-platform/ LLM Quantization Algorithm: https://picovoice.ai/blog/picollm-towards-optimal-llm-quanti... LLM Inference Engine: https://picovoice.ai/blog/picollm-inference-engine-for-x-bit...
kenarsa
·2 年前·議論
Reflecting on Ilya Sutskever's early contribution to DL. This paper saved my job a decade ago
kenarsa
·2 年前·議論
100% of AVX/AVX2 have 256 SIMD registers, and Arm also has non-NEON registers, which are 256/512. of course, this requires runtime detection, but that is ok because even for native code, people need to do that.
kenarsa
·2 年前·議論
"Know" is a vague word. Everyone should know one language inside out as if they can code within a Notepad without IDE support. I think if you know three languages really well, that puts you in the top 1% of devs. I would go for C, Python, and JS.
kenarsa
·2 年前·議論
It's interesting to see the cycle. Alexa said everyone wanted to toggle the lights and get the weather forecast. Hence, they folded. Now, we are back with "stronger" tech and want people to change their behavior.
kenarsa
·4 年前·議論
Have you noted that the board has no connectivity chip? If I had a way to connect to internet without the required chip I had a better story to tell. You snippet of FAQ is correct for all other platforms we support aside from microcontrollers ...

[1] https://www.st.com/en/evaluation-tools/stm32f4discovery.html
kenarsa
·4 年前·議論
Picovoice runs on almost anything: web browsers, mobile, desktop, single board computers, and microcontrollers. For the platforms that have connectivity (i.e. almost anything aside from microcontrollers), we do call home for license management. This helps us keep the `Free Tier` free for personal users, hackers , and skunkworks projects, but make sure we get paid by enterprise customers with deployments at scale [1]. On a microcontroller like the one in this tutorial, there is NO connectivity option. Hence, in this specific case it is 100% offline with no license management. In other cases voice recognition is 100% offline but the call home for license management needs connectivity.

[1] https://picovoice.ai/pricing/
kenarsa
·4 年前·議論
Yes, the board does not have a connectivity chip of any sort [1]. Even if one really wants to there is no way to connect to anything from this board.

[1] https://www.st.com/en/evaluation-tools/stm32f4discovery.html
kenarsa
·4 年前·議論
context, context, and context!! Then deep learning tricks and efficient implementation.

[1] https://picovoice.ai/blog/end-to-end-intent-inference-from-s...
kenarsa
·4 年前·議論
would love to check out what you build with it :) I've been constantly and pleasantly surprised but what people can build given this tech
kenarsa
·4 年前·議論
Yeah, I post about my company that I founded and I am super into it. Which part of this is MISLEADING? The fact that I care or are you saying Picovoice's tech doesn't work? I made the latter easy cause you can now go and try it without me in your way. You comment is misleading.
kenarsa
·4 年前·議論
I'm sure smart people can find a way to hack this! But check my other comment, the chip does NOT have connectivity module. Don't take it from me. Read the ST's product spec.

[1] https://www.st.com/en/evaluation-tools/stm32f4discovery.html
kenarsa
·4 年前·議論
have you noted that there is `Free Tier` that cost you $0? You can train using that. For this tutorial the cost of board ($20) is all you need to pay. Same for personal projects and even small skunkworks projects within companies. Picovoice makes money from large-scale deployments done by device makers

[1] https://picovoice.ai/pricing/
kenarsa
·4 年前·議論
That board doesn't have connectivity! If we had a way to connect to the internet without a connectivity chip I would have had a more exciting post!
kenarsa
·4 年前·議論
The benchmark is using the latest stable of DS >>> https://github.com/Picovoice/speech-to-text-benchmark/blob/m...

the data for cloud-based is from 2022.
kenarsa
·4 年前·議論
mycroft already integrated our wake word (porcupine). we remain neutral and anyone can use our tech :)