Audio-Visual TV Broadcast Signal Segmentation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24220%2F20%3A00007158" target="_blank" >RIV/46747885:24220/20:00007158 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-030-31964-9_21" target="_blank" >http://dx.doi.org/10.1007/978-3-030-31964-9_21</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-31964-9_21" target="_blank" >10.1007/978-3-030-31964-9_21</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Audio-Visual TV Broadcast Signal Segmentation

Popis výsledku v původním jazyce

Research in the field of audio-visual broadcast programs transcription and indexing has been solved for more than 20 years. Great progress has been made mainly in the area of broadcast transcription from audio signal. In the last 10 years, this research has become more intense, mainly due to the use of deep or convolutional neural networks and because of large IT companies (Google, Microsoft, IBM, Amazon) that can rely on a large number of custom embedded multimedia databases. Very important part of system for audio-visual broadcast signal transcription is subsystem for signal segmentation. Signal segmentation is usually solved separately for audio and visual signal. In this paper, a methodology for audio-visual broadcast signal segmentation is presented and described. The result from audio signal segmentation is used for improving of visual signal segmentation.

Název v anglickém jazyce

Audio-Visual TV Broadcast Signal Segmentation

Popis výsledku anglicky

Research in the field of audio-visual broadcast programs transcription and indexing has been solved for more than 20 years. Great progress has been made mainly in the area of broadcast transcription from audio signal. In the last 10 years, this research has become more intense, mainly due to the use of deep or convolutional neural networks and because of large IT companies (Google, Microsoft, IBM, Amazon) that can rely on a large number of custom embedded multimedia databases. Very important part of system for audio-visual broadcast signal transcription is subsystem for signal segmentation. Signal segmentation is usually solved separately for audio and visual signal. In this paper, a methodology for audio-visual broadcast signal segmentation is presented and described. The result from audio signal segmentation is used for improving of visual signal segmentation.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/TH03010018" target="_blank" >TH03010018: DeepSpot - Multilingvální technologie pro detekci a včasné upozornění</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Advances in Intelligent Systems and Computing. 6th International Conference on Man-Machine Interactions

ISBN

978-303031963-2

ISSN

2194-5357

e-ISSN

—

Počet stran výsledku

8

Strana od-do

221-228

Název nakladatele

Springer

Místo vydání

Germany

Místo konání akce

Cracow, Poland

Datum konání akce

1. 1. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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