Algorithms for NLP CS 11711, Fall 2019 Lecture 21: Machine - PowerPoint PPT Presentation

Dec 25, 2022 •188 likes •1.6k views

Algorithms for NLP CS 11711, Fall 2019 Lecture 21: Machine Translation I Yulia Tsvetkov 1 Machine Translation from Dream of the Red Chamber Cao Xue Qin (1792) English: leg, foot, paw French: jambe, pied, patte, etape Challenges Ambiguities

Finding the Viterbi Alignment
Finding the Viterbi Alignment
Finding the Viterbi Alignment
Finding the Viterbi Alignment
Finding the Viterbi Alignment
Finding the Viterbi Alignment

Recommend

SI485i : NLP Missing Topics and the Future Who cares about NLP? NLP has expanded quickly

SI485i : NLP Missing Topics and the Future Who cares about NLP? NLP has expanded quickly Most top-tier universities now have NLP faculty (Stanford, Cornell, Berkeley, MIT, UPenn, CMU, Hopkins, etc) Commercial NLP hiring: Google,

382 views • 24 slides

SI425 : NLP Missing Topics and the Future Who cares about NLP? NLP has expanded quickly

SI425 : NLP Missing Topics and the Future Who cares about NLP? NLP has expanded quickly Most top-tier universities now have NLP faculty (Stanford, Cornell, Berkeley, MIT, UPenn, CMU, Hopkins, etc) Commercial NLP hiring: Google,

541 views • 25 slides

NLP: Two pictures Wordnet and Word Sense Problem NLP Disambiguation Semantics NLP Trinity

7/13/2012 NLP: Two pictures Wordnet and Word Sense Problem NLP Disambiguation Semantics NLP Trinity Parsing Part of Speech Lecture delivered at the summer school on NLP, IIIT Hyderabad, Tagging 10July, 2012 Vision Speech Morph

523 views • 39 slides

Recurrent Neural Networks Graham Neubig Site https://phontron.com/class/nn4nlp2017/ NLP and

CS11-747 Neural Networks for NLP Recurrent Neural Networks Graham Neubig Site https://phontron.com/class/nn4nlp2017/ NLP and Sequential Data NLP and Sequential Data NLP is full of sequential data NLP and Sequential Data NLP is full of

2.05k views • 171 slides

Natural Language Processing (NLP) In 11-711 Algorithms for NLP we take an

Natural Language Processing (NLP) In 11-711 Algorithms for NLP we take an English-centric approach to NLP This enables us to work with a language that all of us understand and focus on core algorithms and tasks Even

370 views • 15 slides

Ontologies for NLP NLP for Ontologies FOIS 2014 - LogOnto Workshop on Logics and Ontologies for

Ontologies for NLP NLP for Ontologies FOIS 2014 - LogOnto Workshop on Logics and Ontologies for Natural Language Overview NLP for Ontologies Ontologies for NLP Portuguese resources Research at PUCRS Introduction We think and we

764 views • 71 slides

Algorithms for NLP 11-711, Fall 2019 Lecture 26: Computational Ethics Yulia Tsvetkov 1

Algorithms for NLP 11-711, Fall 2019 Lecture 26: Computational Ethics Yulia Tsvetkov 1 Tsvetkov Socially Responsible NLP What NLP Has To Do With Ethics? Applications Machine Translation Information Retrieval

1.04k views • 89 slides

Algorithms for NLP IITP, Fall 2019 Lecture 25: Computational Ethics Yulia Tsvetkov 1 Tsvetkov

Algorithms for NLP IITP, Fall 2019 Lecture 25: Computational Ethics Yulia Tsvetkov 1 Tsvetkov Socially Responsible NLP What NLP Has To Do With Ethics? Applications Machine Translation Information Retrieval Question

1.36k views • 89 slides

Facing NLP German Rigau i Claramunt http://adimen.si.ehu.es/~rigau IXA group Departamento de

Facing NLP German Rigau i Claramunt http://adimen.si.ehu.es/~rigau IXA group Departamento de Lenguajes y Sistemas Informticos UPV/EHU AI and NLP Facing NLP From Cyc (adapted) (I) Fred saw the plane flying over Zurich. AI and NLP 2

487 views • 24 slides

IXA pipes: Efficient and Ready to Use Multilingual NLP tools Rodrigo Agerri IXA NLP Group,

IXA pipes: Efficient and Ready to Use Multilingual NLP tools Rodrigo Agerri IXA NLP Group, UPV/EHU OpenNLP project, Apache Software Foundation Rodrigo Agerri (IXA NLP Group, UPV/EHU OpenNLP project, Apache Software Foundation) IXA pipes:

589 views • 21 slides

Prominent Research Directions in NLP Alexander Panchenko Assistant Professor for NLP About

Prominent Research Directions in NLP Alexander Panchenko Assistant Professor for NLP About myself: a decade of fun R&D in NLP 2002-2008: Bauman Moscow State Technical University , Engineer in Information Systems, MOSCOW 2008: Xerox

278 views • 25 slides

Deep Learning for NLP Kiran Vodrahalli Feb 11, 2015 Overview What is NLP? Natural

Deep Learning for NLP Kiran Vodrahalli Feb 11, 2015 Overview What is NLP? Natural Language Processing We try to extract meaning from text: sentiment, word sense, semantic similarity, etc. How does Deep Learning relate? NLP

2.03k views • 124 slides

Hybrid NLP Hybrid NLP O UTLINE O UTLINE Problems of Deep and Shallow Processing

Hybrid NLP Hybrid NLP O UTLINE O UTLINE Problems of Deep and Shallow Processing Hybrid Architectures An Advanced Platform for Hybrid NLP: Deep Thought Applications for Hybrid Processing Conclusion and Outlook LTII

642 views • 25 slides

NLP Programming Tutorial 4 - Word Segmentation Graham Neubig Nara Institute of Science and

NLP Programming Tutorial 4 Word Segmentation NLP Programming Tutorial 4 - Word Segmentation Graham Neubig Nara Institute of Science and Technology (NAIST) 1 NLP Programming Tutorial 4 Word Segmentation Introduction 2 NLP Programming

1.07k views • 43 slides

SI485i : NLP Set 12 Features and Prediction What is NLP, really? Many of our tasks boil down

SI485i : NLP Set 12 Features and Prediction What is NLP, really? Many of our tasks boil down to finding intelligent features of language. We do lots of machine learning over features NLP researchers also use linguistic insights, deep

326 views • 18 slides

Capsule Networks for NLP Will Merrill Advanced NLP 10/25/18 Capsule Networks: A Better ConvNet

Capsule Networks for NLP Will Merrill Advanced NLP 10/25/18 Capsule Networks: A Better ConvNet Architecture proposed by Hinton as a replacement for ConvNets in computer vision Several recent papers applying them to NLP: Zhao

674 views • 64 slides

ARCHER/RDF Overview How do they fit together? Andy Turner, EPCC a.turner@epcc.ed.ac.uk

ARCHER/RDF Overview How do they fit together? Andy Turner, EPCC a.turner@epcc.ed.ac.uk www.epcc.ed.ac.uk www.archer.ac.uk Outline ARCHER/RDF Layout Available file systems Compute resources ARCHER Compute Nodes ARCHER

179 views • 17 slides

Algorithm Engineering (aka. How to Write Fast Code) CS26 S260 Lecture cture 6 Yan n Gu

Algorithm Engineering (aka. How to Write Fast Code) CS26 S260 Lecture cture 6 Yan n Gu I/O Algorithms and Parallel Samplesort The I/O Model CS260: Algorithm Sampling in Algorithm Design Engineering Lecture 6 Parallel Samplesort 2

568 views • 28 slides

Towards A Parallel and Restartable Data Transfer Mechanism in iRODS Zoey Greer Jason Coposky

Towards A Parallel and Restartable Data Transfer Mechanism in iRODS Zoey Greer Jason Coposky Terrell Russell Hao Xu June 5, 2018 Introduction Current iRODS implementation supports limit parallel transfer and restart capability. We

194 views • 16 slides

Computer Graphics Seminar MTAT.03.305 Spring 2015 Raimond Tunnel Conclusion Geometry Front

Computer Graphics Seminar MTAT.03.305 Spring 2015 Raimond Tunnel Conclusion Geometry Front face or back face? Point location in space Vector direction in space Polygons Simple vs non-simple Convex vs concave

518 views • 49 slides

Portable Parallel I/O Handling large datasets in heterogeneous parallel environments May 21,

Mitglied der Helmholtz-Gemeinschaft Portable Parallel I/O Handling large datasets in heterogeneous parallel environments May 21, 2014 Michael Stephan Mitglied der Helmholtz-Gemeinschaft Portable Parallel I/O Part I: HDF5 May 21, 2014

897 views • 66 slides

Extracting Semantic Transfer Rules from Parallel Corpora with SMT Phrase Aligners Petter

Semantic Transfer Two Methods of Rule Extraction Experiment and Results Discussion Conclusion References Extracting Semantic Transfer Rules from Parallel Corpora with SMT Phrase Aligners Petter Haugereid and Francis Bond Linguistics and

610 views • 46 slides

How to Write a Parallel GPU Application Using CUDA and Charm++ Presented by Lukasz Wesolowski

How to Write a Parallel GPU Application Using CUDA and Charm++ Presented by Lukasz Wesolowski Outline GPGPUs and CUDA Requirements for a GPGPU API (from a Charm++ standpoint) CUDA stream approach Charm++ GPU Manager 2 General

562 views • 11 slides

1 MPI-based SILC system Data transfer: the sequential case Currently based on a client-server

Outline Workshop on State-of-the-Art in Scientific and Parallel Computing (PARA '06) Ume, Sweden, June 18-21, 2006 Background Ways of using matrix computation libraries Distributed SILC: An easy-to-use Distributed SILC interface

235 views • 4 slides

Download document

More recommend

Explore More Topics

Stay informed with curated content and fresh updates.

animals pets art culture automotive transportation business finance computer internet construction architecture education-career electronics communication