Comments URL: https://news.ycombinator.com/item?id=47719512

Points: 4

# Comments: 3

Comments URL: https://news.ycombinator.com/item?id=47332883

Points: 48

# Comments: 9

https://news.ycombinator.com/item?id=5409914

If anyone finds this useful I'll probably add some parsing for non-text formats like PDF, images, videos.

Repo: https://github.com/christiansafka/nextjs-rag

Comments URL: https://news.ycombinator.com/item?id=45450001

Points: 3

# Comments: 1

TL:DR During an online meeting, the app instantly transcribes and translates all audio you hear, and allows you to decide when you translate your voice and when you don't. It's invisible to others (like Granola), and works everywhere without any meeting bots. Try it at startpinch.com

Here's a live demo we recorded this morning, without cuts: https://youtu.be/ltM2p-SosLc

When we first launched Pinch, we shipped a video conferencing solution with a human-like AI interpreter that was an active participant in your call. Our users hold the spacebar down while speaking to the translator, and when they release the spacebar the translator speaks out to the entire room.

That design was intentional - it puts the task of context selection on the user and prevents people from interrupting each other awkwardly (only one person can press spacebar at a time). It also comes with heavy tradeoffs, namely:

* Latency - Up to 2x longer meeting lengths due to everyone hearing your full sentence and then the translation of your full sentence

* Friction with first-time users - Customers using Pinch for external communication often meet with new people each time, and we've learned of several that send out an instruction doc pre-meeting on how to join and use translation in the Pinch call. Bad signal for our UX.

* Restricting our customers to those who are meeting creators

Benefits of the desktop app:

1. It creates a virtual microphone that you can use in any meeting app

2. Instant transcription+translation means you can understand what's going on in real-time and interrupt where necessary

3. Simultaneous translation - after you start speaking, the others will hear your translated audio as fast as we can generate it, without interrupting your flow.

Over the last months our focus has been on developing a model and UX to support high translation accuracy while automating context selection - knowing exactly when it has enough words to start the translated sentence. We’ve rolled this out to the desktop app first.

We're incredibly excited to go public beta today, you can give it a try at www.startpinch.com

Cheers, - Christian

Comments URL: https://news.ycombinator.com/item?id=44961153

Points: 65

# Comments: 23

Also in case you're interested in the logistics of using us for livestreaming: If our current platform won't work for your use-case and you need to use OBS + a virtual camera, it's on our roadmap.

From the technical side, speech to speech models have more potential for accuracy (no explicit ASR, no audio->text information loss). We have a few options on mimic'ing nonverbal elements - we could decide when to naturally mix in the original audio, or train our end to end model to handle those nonverbal audio chunks. We'll be trying both but likely the first option on the sooner side!