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Found 7 papers, 1 papers with code
Heterogeneity over Homogeneity: Investigating Multilingual Speech Pre-Trained Models for Detecting Audio Deepfake
To validate our hypothesis, we extract representations from state-of-the-art (SOTA) PTMs including monolingual, multilingual as well as PTMs trained for speaker and emotion recognition, and evaluated them on ASVSpoof 2019 (ASV), In-the-Wild (ITW), and DECRO benchmark databases.
From Text to Transformation: A Comprehensive Review of Large Language Models' Versatility
This groundbreaking study explores the expanse of Large Language Models (LLMs), such as Generative Pre-Trained Transformer (GPT) and Bidirectional Encoder Representations from Transformers (BERT) across varied domains ranging from technology, finance, healthcare to education.
How Paralingual are Paralinguistic Representations? A Case Study in Speech Emotion Recognition
We also show that downstream models using TRILLsson representations achieve SOTA performance in terms of accuracy across various multi-lingual datasets.
Detection of a facemask in real-time using deep learning methods: Prevention of Covid 19
By the end of April 2021, the world has recorded 144, 358, 956 confirmed cases of novel-coronavirus disease (Covid-19) including 3, 066, 113 deaths according to the world health organization (WHO).
From Simulations to Reality: Enhancing Multi-Robot Exploration for Urban Search and Rescue
In this study, we present a novel hybrid algorithm, combining Levy Flight (LF) and Particle Swarm Optimization (PSO) (LF-PSO), tailored for efficient multi-robot exploration in unknown environments with limited communication and no global positioning information.
MLOps: A Review
Recently, Machine Learning (ML) has become a widely accepted method for significant progress that is rapidly evolving.
Roulette-Wheel Selection-Based PSO Algorithm for Solving the Vehicle Routing Problem with Time Windows
The well-known Vehicle Routing Problem with Time Windows (VRPTW) aims to reduce the cost of moving goods between several destinations while accommodating constraints like set time windows for certain locations and vehicle capacity.
