Paper Reading AI Learner

Classification of Vocal Bursts for ACII 2022 A-VB-Type Competition using Convolutional Network Networks and Deep Acoustic Embeddings

2022-09-29 14:58:23
Muhammad Shehram Shah Syed, Zafi Sherhan Syed, Abbas Syed
arXiv_SD
         
Abstract

This report provides a brief description of our proposed solution for the Vocal Burst Type classification task of the ACII 2022 Affective Vocal Bursts (A-VB) Competition. We experimented with two approaches as part of our solution for the task at hand. The first of which is based on convolutional neural networks trained on Mel Spectrograms, and the second is based on average pooling of deep acoustic embeddings from a pretrained wav2vec2 model. Our best performing model achieves an unweighted average recall (UAR) of 0.5190 for the test partition, compared to the chance-level UAR of 0.1250 and a baseline of 0.4172. Thus, an improvement of around 20% over the challenge baseline. The results reported in this document demonstrate the efficacy of our proposed approaches to solve the AV-B Type Classification task.

Abstract (translated)

URL

https://arxiv.org/abs/2209.14842

PDF

https://arxiv.org/pdf/2209.14842.pdf

Tags
3D Action Action_Localization Action_Recognition Activity Adversarial Agent Attention Autonomous Bert Boundary_Detection Caption Chat Classification CNN Compressive_Sensing Contour Contrastive_Learning Deep_Learning Denoising Detection Dialog Diffusion Drone Dynamic_Memory_Network Edge_Detection Embedding Embodied Emotion Enhancement Face Face_Detection Face_Recognition Facial_Landmark Few-Shot Gait_Recognition GAN Gaze_Estimation Gesture Gradient_Descent Handwriting Human_Parsing Image_Caption Image_Classification Image_Compression Image_Enhancement Image_Generation Image_Matting Image_Retrieval Inference Inpainting Intelligent_Chip Knowledge Knowledge_Graph Language_Model Matching Medical Memory_Networks Multi_Modal Multi_Task NAS NMT Object_Detection Object_Tracking OCR Ontology Optical_Character Optical_Flow Optimization Person_Re-identification Point_Cloud Portrait_Generation Pose Pose_Estimation Prediction QA Quantitative Quantitative_Finance Quantization Re-identification Recognition Recommendation Reconstruction Regularization Reinforcement_Learning Relation Relation_Extraction Represenation Represenation_Learning Restoration Review RNN Salient Scene_Classification Scene_Generation Scene_Parsing Scene_Text Segmentation Self-Supervised Semantic_Instance_Segmentation Semantic_Segmentation Semi_Global Semi_Supervised Sence_graph Sentiment Sentiment_Classification Sketch SLAM Sparse Speech Speech_Recognition Style_Transfer Summarization Super_Resolution Surveillance Survey Text_Classification Text_Generation Tracking Transfer_Learning Transformer Unsupervised Video_Caption Video_Classification Video_Indexing Video_Prediction Video_Retrieval Visual_Relation VQA Weakly_Supervised Zero-Shot