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Deep Learning Researcher - Vancouver - Onsite

https://picovoice.ai/careers/deep-learning-researcher/

Picovoice is the only all-in-one on-device voice AI platform with offerings including wake word, speech-to-text, LLM, text-to-speech, and more. All on-device. Runs across mobile, web, desktop, and embedded.


thank you!

prompt engineering is a thing, and it's not a thing that you get on social media posts with emojis or multiple images.

is it a public-facing product?



picovoice processes on the device and you can fine-tune the models https://picovoice.ai/platform/cat/


if you're running it locally, they don't and cannot.

if you're using the hosted whisper, they can. however, they don't specifically talk about it.


https://picovoice.ai/careers/applied-speech-scientist/

Picovoice is a deep tech startup founded by engineers and driven by engineers. We are accelerating the transition of voice AI from the cloud to the edge. Why? Privacy, reliability, and the environment. Numerous enterprises, including NASA and Stanford University, are leveraging Picovoice technology in their products.

In this role, you get to work on

Applied research to improve the accuracy and runtime efficiency of on-device voice recognition (https://picovoice.ai/blog/local-speech-to-text-with-cloud-le..., https://picovoice.ai/blog/end-to-end-intent-inference-from-s..., https://picovoice.ai/blog/direct-speech-indexing/)

Build Voice AI models from scratch for upcoming products

Improve existing Voice AI models: Leopard & Cheetah Speech-to-Text, Octopus Speech-to-Index, Rhino Speech-to-Intent, Porcupine Wake Word Detection, and Cobra Voice Activity Detection

Develop algorithms for automated data gathering and generation

Canada - Vancouver | On-site


Amazon has been working on on-device voice for a while. Actually everyone is trying to do that. Running large speech models in the cloud is expensive, considering the number of devices, they probably need more than "surplus" :)

https://www.amazon.science/blog/on-device-speech-processing-...


It could certainly rack up a big bill.

This is also part of the work that Apple has done (and is likely part of the making Siri cost less for cloud compute).

https://www.macrumors.com/how-to/use-siri-offline-ios/

> In iOS 15, Apple moved all Siri speech processing and personalization onto your device, making the virtual assistant more secure and faster at processing requests. This also means Siri can now handle a range of requests entirely offline.

> Once you're using iOS 15, you don't need to enable anything for Siri to work offline. The types of requests that it can handle without phoning home to Apple's servers include the following:

    Create and disable timers and alarms.
    Launch apps.
    Control Apple Music and Podcasts audio playback.
    Control system settings including accessibility features, volume, Low Power mode, Airplane mode, and so on.


I didnt disclose as I was not gonna promote anything, but I work for a startup specializing in on-device voice recognition. I am 100% biased towards on-device voice processing :)

i just wanted to share my 2 cents, as it's not unique to Apple and the cloud can be costly even if you own it. Big tech has been investing in on-device for a while. besides voice commands, apple and google do transcription locally too. because now you can have local speech to text with cloud level accuracy and of all the reasons you shared - cost, privacy, latency etc. (but again, i'm biased)

https://www.androidauthority.com/voice-typing-opinion-322134... https://techcrunch.com/2022/05/17/apple-adds-live-captions-t...


Interesting! Is that also the case for the homepod (and homepod mini which I have)?


Tutorial on adding subtitles to videos using the Picovoice Leopard Speech-to-Text Python SDK.

1. Install the software 2. Run the code to convert video to text 3. Create an SRT (SubRip subtitle) file

Example: Adding subtitles to a video on YouTube with pytube.

This tutorial requires Picovoice Console account- free to create, allows free transcription for up to 100 hours/month. Processes voice data locally on the device.



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