Guide To VGG-SOUND Datasets For Visual-Audio Recognition

Guide To VGG-SOUND #Datasets For Visual-Audio Recognition
https://zcu.io/008n

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Guide To VGG-SOUND Datasets For Visual-Audio Recognition

VGG-SOUND Datasets is Developed by VGG, Department of Engineering Science, University of Oxford, UK Audio VGGSound Dataset has set a benchmark for audio recognition with visuals. It contains more than 210 k videos with visual and audio. The dataset contains over 310 categorie and 550 hours of video. It is available to download for commercial/research purposes. The VGGSound dataset consists of each video and audio segment being 10 seconds long.

Andrew Zisserman, Andrea Vedaldi is Principal Researchers of VGG(Visual Geometry Group). The VGG-Sound researcher Honglie Chen, Weidi Xie, Andrea Vedaldi and Andrew Zisserman are the core members of VGG, Department of Engineering Science, University of Oxford, UK, published on ICASSP, 2020.

#developers corner #audio #dataset #numpy #pandas #pytorch

Inside ABCD, A Dataset To Build In-Depth Task-Oriented Dialogue Systems

According to a recent study, call centre agents’ spend approximately 82 percent of their total time looking at step-by-step guides, customer data, and knowledge base articles.

Traditionally, dialogue state tracking (DST) has served as a way to determine what a caller wants at a given point in a conversation. Unfortunately, these aspects are not accounted for in popular DST benchmarks. DST is the core part of a spoken dialogue system. It estimates the beliefs of possible user’s goals at every dialogue turn.

To reduce the burden on call centre agents and improve the SOTA of task-oriented dialogue systems, AI-powered customer service company ASAPP recently launched an action-based conversations dataset (ABCD). The dataset is designed to help develop task-oriented dialogue systems for customer service applications. ABCD consists of a fully labelled dataset with over 10,000 human dialogues containing 55 distinct user intents requiring sequences of actions constrained by company policies to accomplish tasks.

https://twitter.com/asapp/status/1397928363923177472

The dataset is currently available on GitHub.

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Guide To VGG-SOUND Datasets For Visual-Audio Recognition

Guide To VGG-SOUND #Datasets For Visual-Audio Recognition
https://zcu.io/008n

#big-data #analytics #tutorial #data-science #datascientist #kaggle

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Data Visualization Guide - Over Time Visuals

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