This is where I store files and documents relating to my graduation project

Re-Implementation of Google Research's VGGish model used for extracting audio features using Pytorch with GPU support.

SERVER: Multi-modal Speech Emotion Recognition using Transformer-based and Vision-based Embeddings

My music tech thesis prototype as well as recent class project

Query service to serve the JibJib TensorFlow model

🏆 🏆 Top-1 Submission to CORSMAL Challenge 2020 (at ICPR). The winning solution for the CORSMAL Challenge (on Intelligent Sensing Summer School 2020)

Machine learning model for bird songs recognition

A VGGish-based DNN trained on the Watkins Marine Mammal Sound Database, with transfer learning from Audioset, to detect multiple marine mammal species.

Audio classification with VGGish as feature extractor in TensorFlow

Pytorch port of Google Research's VGGish model used for extracting audio features.

Extract video features from raw videos using multiple GPUs. We support RAFT flow frames as well as S3D, I3D, R(2+1)D, VGGish, CLIP, and TIMM models.