Realtime Sentiment Analysis and Context-Aware Backchanneling
tomo/CTO at Noxx@tomoima525
0:34This project analyzes sentiment in real-time and provides context-aware backchanneling responses during conversations.
Got access to @typesafeai Jev and the first thing I tried out was the realtime sentiment analysis and context-aware backchanneling with @pipecat_ai . How it works:
- Jev evaluates the turn and sentiments. Sending many instructions in a single call, and it just returns immediately
- Reads interim text every 100-200 sec while I'm talking and responds to what I say. It handles two things
1. react now? as Noul (true/false)
2. speculative reaction, e.g. "neutral continuer" => "mmhmm", "surprising" => "oh wow", "understanding" => "I see"
When 1 is true then 2 is triggered with LLMTextFrame
The result is surprisingly good with low latency (100 - 300 ms) I feel more natural
LLM-based turn strategy is at the next level!