The Reality of Multi-Lingual Machine Translation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10456894" target="_blank" >RIV/00216208:11320/21:10456894 - isvavai.cz</a>

Výsledek na webu

<a href="http://ufal.mff.cuni.cz/biblio/attachments/2021-kocmi-m7555028765394592558.pdf" target="_blank" >http://ufal.mff.cuni.cz/biblio/attachments/2021-kocmi-m7555028765394592558.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

The Reality of Multi-Lingual Machine Translation

Popis výsledku v původním jazyce

Our book &quot;The Reality of Multi-Lingual Machine Translation&quot; discusses the benefits and perils of using more than two languages in machine translation systems. While focused on the particular task of sequence-to-sequence processing and multi-task learning, the book targets somewhat beyond the area of natural language processing. Machine translation is for us a prime example of deep learning applications where human skills and learning capabilities are taken as a benchmark that many try to match and surpass. We document that some of the gains observed in multi-lingual translation may result from simpler effects than the assumed cross-lingual transfer of knowledge. In the first, rather general part, the book will lead you through the motivation for multi-linguality, the versatility of deep neural networks especially in sequence-to-sequence tasks to complications of this learning. We conclude the general part with warnings against too optimistic and unjustified explanations of the gains that neural networ

Název v anglickém jazyce

The Reality of Multi-Lingual Machine Translation

Popis výsledku anglicky

Our book &quot;The Reality of Multi-Lingual Machine Translation&quot; discusses the benefits and perils of using more than two languages in machine translation systems. While focused on the particular task of sequence-to-sequence processing and multi-task learning, the book targets somewhat beyond the area of natural language processing. Machine translation is for us a prime example of deep learning applications where human skills and learning capabilities are taken as a benchmark that many try to match and surpass. We document that some of the gains observed in multi-lingual translation may result from simpler effects than the assumed cross-lingual transfer of knowledge. In the first, rather general part, the book will lead you through the motivation for multi-linguality, the versatility of deep neural networks especially in sequence-to-sequence tasks to complications of this learning. We conclude the general part with warnings against too optimistic and unjustified explanations of the gains that neural networ

Druh

B - Odborná kniha

CEP obor

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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/GA18-24210S" target="_blank" >GA18-24210S: Mnohojazyčný strojový překlad</a><br>

Návaznosti

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

Rok uplatnění

2021

Kód důvěrnosti údajů

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

ISBN

978-80-88132-11-0

Počet stran knihy

199

Název nakladatele

UFAL

Místo vydání

Prague, Czechia

Kód UT WoS knihy

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