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Further tinkering with my little French tutor app. This version is using the Gemini Multimodal Live API. The speech understanding in Gemini is quite something. In this video you can see Gemini correcting my pronunciation. (Very patiently.) The language tutor use case really highlights the strengths of a next-generation...

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kwindla

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13,005 görüntüleme • 1 yıl önce •via X (Twitter)

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kwindla profil fotoğrafı
kwindla1 yıl önce

Code is here: Here are the docs for Pipecat's open source client SDKs for javascript, React, iOS, Android, React Native, and C++: The Pipecat clients all support WebRTC, WebSocket, and HTTP network transports.

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Nexus 👾1 yıl önce

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The Canaanite profil fotoğrafı
The Canaanite1 yıl önce

bravo, excellente prononciation monsieur 🤣

عای‌ خان profil fotoğrafı
عای‌ خان1 yıl önce

Amazing. I need to code up a Maths tutor for my kids for those inevitable times where my patience sadly failed. 😅

Emanuel Perez profil fotoğrafı
Emanuel Perez1 yıl önce

Whoa

Samuel Ekpe profil fotoğrafı
Samuel Ekpe1 yıl önce

interesting

Mitja Martini profil fotoğrafı
Mitja Martini1 yıl önce

Thanks for sharing this very nice use case! I've been using ChatGPT with my daughter to help her learning Latin, not in voice mode, though :)

Nicolas MICHEL profil fotoğrafı
Nicolas MICHEL1 yıl önce

it is funny, the machine has an African accent. This will lead to some funny situations if you start speaking in public with this accent 😂

Jake profil fotoğrafı
Jake1 yıl önce

cool any other interesting uncommon use cases? I feel like the voice use cases are going to blow up this year

kwindla profil fotoğrafı
kwindla1 yıl önce

> any other interesting uncommon use cases? Check out the voice interaction experiments that @trudypainter has been posting!

Dan Goodman 🍊 profil fotoğrafı
Dan Goodman 🍊1 yıl önce

Can you have it take in audio but output text in pipecat?

kwindla profil fotoğrafı
kwindla1 yıl önce

> Can you have it take in audio but output text in pipecat? Yes!

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Really happy to see the interest around our “Hands-on with Gemini” video. In our developer blog yesterday, we broke down how Gemini was used to create it. We gave Gemini sequences of different modalities — image and text in this case — and had it respond by predicting what might come next. Devs can try similar things when access to Pro opens on 12/13 🚀. The knitting demo used Ultra⚡ All the user prompts and outputs in the video are real, shortened for brevity. The video illustrates what the multimodal user experiences built with Gemini could look like. We made it to inspire developers. When you’re building an app, you can get similar results (there’s always some variability with LLMs) by prompting Gemini with an instruction that allows the user to "configure" the behavior of the model, like inputting “you are an expert in science …” before a user can engage in the same kind of back and forth dialogue. Here’s a clip of what this looks like in AI Studio with Gemini Pro. We’ve come a long way since Flamingo 🦩 & PALI, looking forward to seeing what people build with it!

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