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Maximum Entropy Modeling Toolkit [article]

<span title="1996-12-31">1996</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
The Maximum Entropy Modeling Toolkit supports parameter estimation and prediction for statistical language models in the maximum entropy framework.  ...  This manual explains how to build maximum entropy models for discrete domains with the Maximum Entropy Modeling Toolkit (MEMT).  ...  Here we briefly guide you through these three steps in the Maximum Entropy Modeling Toolkit. The first step is to define a set G of features on Y|X.  ...
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/cmp-lg/9612005v1">arXiv:cmp-lg/9612005v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/n75b22qtereznnlk2ym4jshjri">fatcat:n75b22qtereznnlk2ym4jshjri</a> </span>
<a target="_blank" rel="noopener" href="https://archive.org/download/arxiv-cmp-lg9612005/cmp-lg9612005.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> File Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/5b/03/5b038983b55f8f1a65923cd3c01fc0703bcfa47a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/cmp-lg/9612005v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

ACOUSTIC-SYNTACTIC MAXIMUM ENTROPY MODEL FOR AUTOMATIC PROSODY LABELING

Vivek Rangarajan, Shrikanth Narayanan, Srinivas Bangalore
<span title="">2006</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/gfqnwwky7rg6bgki4hedb3iimu" style="color: black;">2006 IEEE Spoken Language Technology Workshop</a> </i> &nbsp;
We model the acoustic-prosodic stream with two different models, one a maximum entropy model and the other a traditional HMM.  ...  We propose a maximum entropy syntacticprosodic model that achieves an accuracy of 85.22% and 91.54% for pitch accent and boundary tone labeling on the Boston University Radio News corpus.  ...  Acknowledgements We would like to thank Vincent Goffin, Stephan Kanthak, Patrick Haffner, Enrico Bocchieri for their support with acoustic modeling tools.  ...
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/slt.2006.326820">doi:10.1109/slt.2006.326820</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/slt/SridharNB06.html">dblp:conf/slt/SridharNB06</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/gd7ew4abtrg5vhs3o5ddts5ddm">fatcat:gd7ew4abtrg5vhs3o5ddts5ddm</a> </span>
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Application of Entity Relation Extraction Method under CRF and Syntax Analysis Tree in the Construction of Military Equipment Knowledge Graph

Chenguang Liu, Yongli Yu, Xingxin Li, Peng Wang
<span title="">2020</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
Then, the relation is classified based on the maximum entropy model.  ...  Entity Relation Extraction Method Based on the Maximum Entropy Model Entity relation extraction method based on maximum entropy model: this is a relation tree-based relation structure that relies on the  ...  Three methods based on the basic expected training library are clarified; that is, the entity relation extraction method based on the maximum entropy model, entity relation extraction method of CRF and  ...
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2020.3034894">doi:10.1109/access.2020.3034894</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/noflw4mck5artfcle3554cfdde">fatcat:noflw4mck5artfcle3554cfdde</a> </span>
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Value Creation by Toolkits for User Innovation and Design: The Case of the Watch Market

Nikolaus Franke, Frank Piller
<span title="">2004</span> <i title="Wiley"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ski7mxviercqjmc34rxjxtu37a" style="color: black;">The Journal of product innovation management</a> </i> &nbsp;
Entropy coefficients showed that self-designed watches vary quite widely.  ...  Toolkits allow customers to create their own product, which in turn is produced by the manufacturer.  ...  The univariate model shows that only the ''strap'' dimension shows a somewhat lower entropy (73.7% of maximum entropy).  ...
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1111/j.0737-6782.2004.00094.x">doi:10.1111/j.0737-6782.2004.00094.x</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/q4zdm2bcnnhgnlgtwaax5ff334">fatcat:q4zdm2bcnnhgnlgtwaax5ff334</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170705062346/http://downloads.mass-customization.de/jpim04.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/25/9e/259e40ef5cf46db516af97f9a6bcd3e1b74172a8.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1111/j.0737-6782.2004.00094.x"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Tagging Funding Agencies and Grants in Scientific Articles using Sequential Learning Models

Subhradeep Kayal, Zubair Afzal, George Tsatsaronis, Sophia Katrenko, Pascal Coupet, Marius Doornenbal, Michelle Gregory
<span title="">2017</span> <i title="Association for Computational Linguistics"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/mmfdumjhkjcwpg2mh5sqan4zsi" style="color: black;">BioNLP 2017</a> </i> &nbsp;
markov models (HMM) and maximum entropy models (MaxEnt), on a benchmark set created in-house.  ...  In this paper we present a solution for tagging funding bodies and grants in scientific articles using a combination of trained sequential learning models, namely conditional random fields (CRF), hidden  ...  Finally, another way of modelling data for NER is Maximum Entropy (MaxEnt) models, which select the probability distribution that maximizes entropy, thereby making as little assumptions about the data  ...
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.18653/v1/w17-2327">doi:10.18653/v1/w17-2327</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/bionlp/KayalATKCDG17.html">dblp:conf/bionlp/KayalATKCDG17</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/hw3327oskneh5lz5aembmyi3l4">fatcat:hw3327oskneh5lz5aembmyi3l4</a> </span>
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A Supervised Approach for Automatic Web Documents Topic Extraction Using Well-Known Web Design Features

Kazem Taghandiki, Ahmad Zaeri, Amirreza Shirani
<span title="2016-11-08">2016</span> <i title="MECS Publisher"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/e2edi7vsvnbf3nx6iy25ioadxe" style="color: black;">International Journal of Modern Education and Computer Science</a> </i> &nbsp;
A topic modeling technique is used over extracted features to build four classifiers-C4.5, Decision Tree, Naï ve Bayes and Maximum Entropy-which are separately adopted to train and test our data.  ...  The Maximum Entropy is based on the Principle of Maximum Entropy which selects the model with the largest entropy.  ...  Then MALLET topic modeling toolkit [4] is used over extracted features to build four classifiers-C4.5, Decision Tree, Naï ve Bayes and Maximum Entropy-which are separately adopted to identify the topics  ...
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5815/ijmecs.2016.11.03">doi:10.5815/ijmecs.2016.11.03</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/lv6vzibf4vdf3h3zkxmo2pjetm">fatcat:lv6vzibf4vdf3h3zkxmo2pjetm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190428194049/http://www.mecs-press.org/ijmecs/ijmecs-v8-n11/IJMECS-V8-N11-3.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/df/cf/dfcfa7be7218b68f8259ffa59248a1173b55a392.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5815/ijmecs.2016.11.03"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Exploiting Acoustic and Syntactic Features for Automatic Prosody Labeling in a Maximum Entropy Framework

V.K. Rangarajan Sridhar, S. Bangalore, S.S. Narayanan
<span title="">2008</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/zcz4ey2iwffxtgaodtf5jtebmy" style="color: black;">IEEE Transactions on Audio, Speech, and Language Processing</a> </i> &nbsp;
The reported results are significantly better than previously reported results and demonstrate the strength of maximum entropy model in jointly modeling simple lexical, syntactic, and acoustic features  ...  The proposed maximum entropy acoustic-syntactic model achieves pitch accent and boundary tone detection accuracies of 86.0% and 93.1% on the Boston University Radio News corpus, and, 79.8% and 90.3% on  ...  Maximum Entropy Model for Break Index Prediction1) Syntactic-Prosodic Model:The maximum entropy syntactic-prosodic model uses only lexical and syntactic information for prosodic break index labeling.  ...
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/tasl.2008.917071">doi:10.1109/tasl.2008.917071</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/19603083">pmid:19603083</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC2709295/">pmcid:PMC2709295</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4khywh3dcrf4nbx3do6mhjlu6a">fatcat:4khywh3dcrf4nbx3do6mhjlu6a</a> </span>
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Advancing Macroecology Using Informatics and Entropy Maximization (NSF Grant #0953694)

Ethan P. White
<span title="2012-08-01">2012</span> <i title="Figshare"> Figshare </i> &nbsp;
Find and test general models for macroecological patterns 2. Explore the use of maximum entropy approaches in ecology 3. Train scientists in core computational methods 4.  ...  Research Objective 1: Evaluate the performance of current maximum entropy models.  ...  RESEARCH OBJECTIVES Objective 1: Evaluate the performance of current maximum entropy models and determine if there are situations in which MaxEnt performs poorly All maximum entropy models published to  ...
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.6084/m9.figshare.93937.v1">doi:10.6084/m9.figshare.93937.v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/666afjoiardghf5ej2jfyfmfr4">fatcat:666afjoiardghf5ej2jfyfmfr4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200214151032/https://s3-eu-west-1.amazonaws.com/pfigshare-u-files/96032/career_proposal.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/47/91/4791e92432fbe465d556b0bd0c98f1ad39c63b7a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.6084/m9.figshare.93937.v1"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> figshare.com </button> </a>

NNVLP: A Neural Network-Based Vietnamese Language Processing Toolkit [article]

Thai-Hoang Pham, Xuan-Khoai Pham, Tuan-Anh Nguyen, Phuong Le-Hong
<span title="2017-10-19">2017</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We provide both API and web demo for this toolkit.  ...  This paper demonstrates neural network-based toolkit namely NNVLP for essential Vietnamese language processing tasks including part-of-speech (POS) tagging, chunking, named entity recognition (NER).  ...  Related Works Previously published systems for Vietnamese language processing used traditional machine learning methods such as Conditional Random Field (CRF), Maximum Entropy Markov Model (MEMM), and  ...
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1708.07241v5">arXiv:1708.07241v5</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/dche2bqdhzgqjpggzfpo6g5rxm">fatcat:dche2bqdhzgqjpggzfpo6g5rxm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200911171313/https://arxiv.org/pdf/1708.07241v5.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/1c/31/1c31b90dacdef91a96fa5024f75db3f1dcfc6647.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1708.07241v5" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Using Maximum Entropy for Automatic Image Annotation [chapter]

Jiwoon Jeon, R. Manmatha
<span title="">2004</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
Since the Maximum Entropy model allows for the use of a large number of predicates to possibly increase performance even further, Maximum Entropy model is a promising model for the task of automatic image  ...  The experimental results show that Maximum Entropy outperforms one of the classical translation models that has been applied to this task and the Cross Media Relevance Model.  ...  We used Zhang Le's publicly available Maximum Entropy Modeling Toolkit [18] .  ...
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-540-27814-6_7">doi:10.1007/978-3-540-27814-6_7</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ockyylxovjfb7odada43ixbzv4">fatcat:ockyylxovjfb7odada43ixbzv4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170706015649/http://ciir-publications.cs.umass.edu/pub/web/getpdf.php?id=500" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/75/bd/75bdefc4f4595a668c20930c935b82fa22d14c9e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-540-27814-6_7"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Confidence Investigation of Discovering Organizational Network Structures Using Transfer Entropy

Joshua Rodewald, John Colombi, Kyle Oyama, Alan Johnson
<span title="">2016</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/cx3f4s3qmfe6bg4qvuy2cxezyu" style="color: black;">Procedia Computer Science</a> </i> &nbsp;
The organizational structures are built using a model developed by Dodd, Watts, et al, and a simulation method for complex adaptive supply networks is used to create node behavior data.  ...  Transfer entropy has long been used to discover network structures and relationships based on the behavior of nodes in the system, especially for complex adaptive systems.  ...  Transfer entropy was calculated for each pair of nodes in the network (in both directions) using the JIDT toolkit.  ...
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.procs.2016.09.294">doi:10.1016/j.procs.2016.09.294</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/pjakpzruxbg2zijtuusy4l7avy">fatcat:pjakpzruxbg2zijtuusy4l7avy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190309224712/https://core.ac.uk/download/pdf/81924083.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/3c/e6/3ce6f44c57e5f27c43c8a48a8640cfe8d6e2df50.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.procs.2016.09.294"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> elsevier.com </button> </a>

A Maximum Entropy Approach to Kannada Part Of Speech Tagging

Shambhavi.B. R, Ramakanth Kumar P, Revanth G
<span title="2012-03-31">2012</span> <i title="Foundation of Computer Science"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/b637noqf3vhmhjevdfk3h5pdsu" style="color: black;">International Journal of Computer Applications</a> </i> &nbsp;
In this paper, the probabilistic classifier technique of Maximum Entropy model is experimented for the tagging of Kannada sentences.  ...  Accuracy of 81.6% was obtained in the experiments which prove that Maximum Entropy is well suited for Kannada language.  ...  MAXIMUM ENTROPY MODEL One of the popularly used probabilistic methods for POS tagging task in Maximum Entropy model [2] .  ...
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5120/5600-7852">doi:10.5120/5600-7852</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/3x6minlkfzeltdodouvmlgrheq">fatcat:3x6minlkfzeltdodouvmlgrheq</a> </span>
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Research on Classification of Topic Sentences Combined with Term Recognition

Hui Liu, Yao Liu
<span title="">2016</span> <i title="ICIC International"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ggvwll4d4nbxdk5zvkllrwev3m" style="color: black;">Innovative Computing Information and Control Express Letters, Part B: Applications</a> </i> &nbsp;
Experimental results show that the precision of classification based on SVM and CRFs is 94.9% which is superior to methods based on other models.  ...  Conditional Random Fields brings together the best of generative models and Maximum Entropy Markov Models.  ...  Results show that Hidden Markov Model recognizes terms with a precision of 8.9 percent, which is better than Maximum Entropy Model.  ...
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.24507/icicelb.07.01.167">doi:10.24507/icicelb.07.01.167</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ujvexwic6zdlpb7s5wngcp2o44">fatcat:ujvexwic6zdlpb7s5wngcp2o44</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220310090229/http://www.icicelb.org/ellb/contents/2016/1/elb-07-01-25.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/78/76/7876d847ee73bef4675e3dbfb812f63f45b3a252.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.24507/icicelb.07.01.167"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Comparing the Performance of Different NLP Toolkits in Formal and Social Media Text

Alexandre Pinto, Hugo Gonçalo Oliveira, Ana Oliveira Alves, Marc Herbstritt
<span title="2016-06-20">2016</span> <i > <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/lnvptykl5re5bcglyz523trhtq" style="color: black;">Symposium on Languages, Applications and Technologies</a> </i> &nbsp;
The obtained results are analyzed and, while we could not decide on a single toolkit, this exercise was very helpful to narrow our choice.  ...  Nowadays, there are many toolkits available for performing common natural language processing tasks, which enable the development of more powerful applications without having to start from scratch.  ...  The Chunker and the NER modules are trained on the ACE corpus with a Maximum Entropy model Table 6 6 Toolkit properties.  ...
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.4230/oasics.slate.2016.3">doi:10.4230/oasics.slate.2016.3</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/slate/PintoOA16.html">dblp:conf/slate/PintoOA16</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/mn2pco57ubc5hop2dsasvz3rai">fatcat:mn2pco57ubc5hop2dsasvz3rai</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220307212253/https://drops.dagstuhl.de/opus/volltexte/2016/6008/pdf/OASIcs-SLATE-2016-3.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/af/7e/af7edf3b24930d0140be0d30870a73a8d7b0dddb.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.4230/oasics.slate.2016.3"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

The IBM Attila speech recognition toolkit

Hagen Soltau, George Saon, Brian Kingsbury
<span title="">2010</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/gfqnwwky7rg6bgki4hedb3iimu" style="color: black;">2010 IEEE Spoken Language Technology Workshop</a> </i> &nbsp;
We describe the design of IBM's Attila speech recognition toolkit.  ...  classes with simple interfaces, an interconnection layer implemented in a modern scripting language (Python), and a standardized collection of scripts for system-building produce a flexible and scalable toolkit  ...  The Decoder can handle several types of the language model, including a new class based Maximum Entropy model described in [18] .  ...
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/slt.2010.5700829">doi:10.1109/slt.2010.5700829</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/slt/SoltauSK10.html">dblp:conf/slt/SoltauSK10</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/iovd5e6abnbvrfpnvm6iml7euq">fatcat:iovd5e6abnbvrfpnvm6iml7euq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170829172741/https://catalog.ldc.upenn.edu/docs/LDC2011T06/AttilaSLT11.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/fc/98/fc988344cbaf8af1ae5c841f71f8c96ed8db1bf7.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/slt.2010.5700829"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>
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