Alien-ware

[ebowwa]

Audio Buffer Emotion Detection:

Integrate a basic ML model (TensorFlow Lite) to analyze speech emotions from the audio buffers, using the WebSocket for live feedback.

Implementation: Send extracted audio features through a lightweight model to infer emotion and send it to WebSocket. Fine-tune parameters to balance performance with low latency requirements.

[ebowwa]

Audio Buffer Adaptive Buffer Segmentation Using Real-Time Analysis:

Algorithm: Dynamically segment audio based on content and buffer length, creating markers for important sections (e.g., speech, silence) and organizing file output accordingly.
Use Case: Organizes long recordings into logical segments, especially for use cases where analysis or playback in specific segments (like pauses or key phrases) is necessary.
Implementation: Create dynamic buffer windows and segment audio based on detected patterns. Integrate markers for important segments, and implement in audioFile for file storage.