Final Year Project for Speech Separation
-
Updated
Oct 3, 2023 - Python
Final Year Project for Speech Separation
This is the code&dataset for our paper [Modeling Attention and Memory for Auditory Selection in a Cocktail Party Environment. AAAI 2018]
Estimate the number of concurrent speakers from single channel mixtures to crack the "cocktail-party” problem.
An Algorithm for Speaker Recognition in a Multi-Speaker Environment
An implementation of the fastICA algorithm for the cocktail party problem
Solves the "Cocktail Party Problem" using ReSpeaker 4-Mic Array & AuxIVA (BSS). Features a real-time AI Tutor pipeline (Whisper + GPT-4o) for simultaneous multi-speaker interaction.
Programming assignments and final project done as part of CS 280 (Intelligent Systems) course as taught in the University of the Philippines - Diliman
Machine Learning coursework | Applied Sciences Faculty, UCU (2019)
🎧 Separate voices in noisy environments with this AI-powered pipeline, enhancing clarity and providing individualized tutoring for each speaker.
Me trying to code a solution to the cocktail party problem
Add a description, image, and links to the cocktail-party-problem topic page so that developers can more easily learn about it.
To associate your repository with the cocktail-party-problem topic, visit your repo's landing page and select "manage topics."