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<!DOCTYPE html>
<html>
<head>
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<meta name="description"
content="OpenAV-dataset">
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<title>OpenAV-dataset</title>
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<section class="hero">
<div class="hero-body">
<div class="container is-max-desktop">
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<div class="column has-text-centered">
<h1 class="title is-1 publication-title">
OpenAV: Dataset for Audio-Visual Voice Control of a Computer for Hand
Disabled People
</h1>
<div class="is-size-5 publication-authors">
<span class="author-block">Authors are hidden for peer review<sup>1</sup></span>
</div>
<div class="is-size-5 publication-authors">
<span class="author-block"><sup>1</sup> Affiliation is hidden for peer review</span>
<br />
<span><a href="https://specom2024.ftn.uns.ac.rs/" target="_blank">SPECOM 2024</a> (submitted)</span>
</div>
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target="_blank"
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<span>Data (coming soon)</span>
</a>
</span>
</div>
</div>
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</div>
</div>
</section>
<section class="section" style="padding: 0; margin:0">
<div class="TODO-section">
<div class="container is-max-desktop">
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<h2 class="title is-5">TODO List</h2>
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</defs>
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<use xlink:href="#todo__circle" class="todo__circle"></use>
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<div class="todo__text">Data collection</div>
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<div class="todo__text">Data labelling</div>
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<div class="todo__text">SPECOM paper submission</div>
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<div class="todo__text">arXiv paper submission (after accepting)</div>
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</svg>
<div class="todo__text">Release code and models (after accepting) </div>
</label>
</div>
</div>
</div>
</div>
</div>
</div>
<div class="abstract-section">
<div class="container is-max-desktop abstract-sect">
<div class="columns is-centered has-text-centered">
<div class="column is-four-fifths">
<h2 class="title is-3">Abstract</h2>
<div class="content has-text-justified">
<p>
In recent years, audio-visual speech recognition (AVSR) assistance systems have gained increasing attention from
researchers as an important part of human-computer interaction (HCI). The objective of this paper is to further advance the
development of assistive technologies in the AVSR field by introducing a multi-modal OpenAV dataset, intended for state-of-the-art neural network model training. The OpenAV is designed to train AVSR models for assistance to persons without
hands or with disabilities of their hands or arms in HCI. The dataset could also be useful for ordinary users at hands-free
contactless HCI. The dataset currently includes the recordings of 15 speakers with a minimum of 10 recording sessions for
each. Along with this we provide a detailed description of the dataset and its collection pipeline. In addition, we evaluate
state-of-the-art audio-visual (AV) speech recognition approach and present a baseline recognition results. We also describe
the recording methodology, release the recording software to public, as well as open the access to the dataset.
</p>
</div>
</div>
</div>
</div>
</div>
<div class="dataset-section">
<div class="container is-max-desktop">
<div class="dataset">
<div class="columns is-centered has-text-centered">
<div class="column is-four-fifths">
<h2 class="title is-3">OpenAV Dataset Description</h2>
<img class="img-method" src="./static/img/dataset.png" alt="method">
</div>
</div>
</div>
</div>
</div>
<div class="examples-section">
<div class="container is-max-desktop">
<div class="examples">
<div class="columns is-centered has-text-centered">
<div class="column is-four-fifths">
<h2 class="title is-3">Snapshots of the Speakers</h2>
<img class="img-method" src="./static/img/examples.png" alt="method">
</div>
</div>
</div>
</div>
</div>
<div class="software-section">
<div class="container is-max-desktop">
<div class="software">
<div class="columns is-centered has-text-centered">
<div class="column is-four-fifths">
<h2 class="title is-3">Web-Service for Recording</h2>
<img class="img-method" src="./static/img/soft.jpg" alt="method">
</div>
</div>
</div>
</div>
</div>
<div class="architectures-section">
<div class="container is-max-desktop">
<div class="architectures">
<div class="columns is-centered has-text-centered">
<div class="column is-four-fifths">
<h2 class="title is-3"> Audio-Visual Neural Network Model Architecture </h2>
<img class="img-method" src="./static/img/architectures.png" alt="method">
</div>
</div>
</div>
</div>
</div>
<div class="conclusion-section">
<div class="container is-max-desktop">
<div class="conclusion">
<div class="columns is-centered has-text-centered">
<div class="column is-four-fifths">
<h2 class="title is-3">Conclusion</h2>
<div class="content has-text-justified">
<p>
In this paper, we have created a multi-speaker audio-visual dataset OpenAV, designed for state-of-the-art
neural network model training and intended for
building AVSR assistance systems for people with
hands disabilities. The dataset could also be useful
for ordinary users at hands-free contactless HCI. The
dataset currently includes the recordings of 15
speakers with a minimum of 10 recording sessions for
each. Along with this we have provided a detailed
description of the dataset and its collection pipeline. </br></br>
In addition, we have evaluated state-of-the-art audio-visual (AV) speech recognition approach and have
presented a baseline recognition results. The fusion
of both audio and visual modalities results in an
accuracy of <b>91.54%</b>, achieved through a model-level
fusion approach. This in terms of recognition accuracy
is comparable to the state-of-the-art results achieved
for other AV corpora.
</p>
</div>
</div>
</div>
</div>
</div>
</div>
</section>
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<p>
This page was built using the <a href="https://github.com/SMIL-SPCRAS/OpenAV-dataset" target="_blank">OpenAV-dataset project page</a>, which was adopted from the <a href="https://nerfies.github.io" target="_blank">Nerfies</a> project page.
You are free to borrow the of this website, we just ask that you link back to this page in the footer. <br> This website is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-sa/4.0/" target="_blank">Creative
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