Somayajulu Sripada

Also published as: Somayajula G. Sripada, Somayajulu G. Sripada, Somayajulu Gowri Sripada


2023

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Enhancing factualness and controllability of Data-to-Text Generation via data Views and constraints
Craig Thomson | Clement Rebuffel | Ehud Reiter | Laure Soulier | Somayajulu Sripada | Patrick Gallinari
Proceedings of the 16th International Natural Language Generation Conference

Neural data-to-text systems lack the control and factual accuracy required to generate useful and insightful summaries of multidimensional data. We propose a solution in the form of data views, where each view describes an entity and its attributes along specific dimensions. A sequence of views can then be used as a high-level schema for document planning, with the neural model handling the complexities of micro-planning and surface realization. We show that our view-based system retains factual accuracy while offering high-level control of output that can be tailored based on user preference or other norms within the domain.

2022

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Error Analysis of ToTTo Table-to-Text Neural NLG Models
Barkavi Sundararajan | Somayajulu Sripada | Ehud Reiter
Proceedings of the 2nd Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)

We report error analysis of outputs from seven Table-to-Text generation models fine-tuned on ToTTo, an open-domain English language dataset. A manual error annotation of a subset of outputs (a total of 5,278 sentences) belonging to the topic of Politics generated by these seven models has been carried out. Our error annotation focused on eight categories of errors. The error analysis shows that more than 45% of sentences from each of the seven models have been error-free. It uncovered some of the specific classes of errors such as WORD errors that are the dominant errors in all the seven models, NAME and NUMBER errors are more committed by two of the GeM benchmark models, whereas DATE-DIMENSION and OTHER category of errors are more common in our Table-to-Text models.

2020

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Studying the Impact of Filling Information Gaps on the Output Quality of Neural Data-to-Text
Craig Thomson | Zhijie Zhao | Somayajulu Sripada
Proceedings of the 13th International Conference on Natural Language Generation

It is unfair to expect neural data-to-text to produce high quality output when there are gaps between system input data and information contained in the training text. Thomson et al. (2020) identify and narrow information gaps in Rotowire, a popular data-to-text dataset. In this paper, we describe a study which finds that a state-of-the-art neural data-to-text system produces higher quality output, according to the information extraction (IE) based metrics, when additional input data is carefully selected from this newly available source. It remains to be shown, however, whether IE metrics used in this study correlate well with humans in judging text quality.

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SportSett:Basketball - A robust and maintainable data-set for Natural Language Generation
Craig Thomson | Ehud Reiter | Somayajulu Sripada
Proceedings of the Workshop on Intelligent Information Processing and Natural Language Generation

2018

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Towards making NLG a voice for interpretable Machine Learning
James Forrest | Somayajulu Sripada | Wei Pang | George Coghill
Proceedings of the 11th International Conference on Natural Language Generation

This paper presents a study to understand the issues related to using NLG to humanise explanations from a popular interpretable machine learning framework called LIME. Our study shows that self-reported rating of NLG explanation was higher than that for a non-NLG explanation. However, when tested for comprehension, the results were not as clear-cut showing the need for performing more studies to uncover the factors responsible for high-quality NLG explanations.

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Comprehension Driven Document Planning in Natural Language Generation Systems
Craig Thomson | Ehud Reiter | Somayajulu Sripada
Proceedings of the 11th International Conference on Natural Language Generation

This paper proposes an approach to NLG system design which focuses on generating output text which can be more easily processed by the reader. Ways in which cognitive theory might be combined with existing NLG techniques are discussed and two simple experiments in content ordering are presented.

2017

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Textually Summarising Incomplete Data
Stephanie Inglis | Ehud Reiter | Somayajulu Sripada
Proceedings of the 10th International Conference on Natural Language Generation

Many data-to-text NLG systems work with data sets which are incomplete, ie some of the data is missing. We have worked with data journalists to understand how they describe incomplete data, and are building NLG algorithms based on these insights. A pilot evaluation showed mixed results, and highlighted several areas where we need to improve our system.

2016

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Absolute and Relative Properties in Geographic Referring Expressions
Rodrigo de Oliveira | Somayajulu Sripada | Ehud Reiter
Proceedings of the 9th International Natural Language Generation conference

2015

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A Simple Surface Realization Engine for Telugu
Sasi Raja Sekhar Dokkara | Suresh Verma Penumathsa | Somayajulu Gowri Sripada
Proceedings of the 15th European Workshop on Natural Language Generation (ENLG)

2014

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A Case Study: NLG meeting Weather Industry Demand for Quality and Quantity of Textual Weather Forecasts
Somayajulu Sripada | Neil Burnett | Ross Turner | John Mastin | Dave Evans
Proceedings of the 8th International Natural Language Generation Conference (INLG)

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Adapting SimpleNLG for Brazilian Portuguese realisation
Rodrigo de Oliveira | Somayajulu Sripada
Proceedings of the 8th International Natural Language Generation Conference (INLG)

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Determining Content for Unknown Users: Lessons from the MinkApp Case Study
Gemma Webster | Chris Mellish | Somayajulu G. Sripada | Rene Van Der Wal | Koen Arts | Yolanda Melero | Xavier Lambin
Proceedings of the 8th International Natural Language Generation Conference (INLG)

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Latent User Models for Online River Information Tailoring
Xiwu Han | Somayajulu Sripada | Kit Macleod | Antonio Ioris
Proceedings of the 8th International Natural Language Generation Conference (INLG)

2012

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MinkApp: Generating Spatio-temporal Summaries for Nature Conservation Volunteers
Nava Tintarev | Yolanda Melero | Somayajulu Sripada | Elizabeth Tait | Rene Van Der Wal | Chris Mellish
INLG 2012 Proceedings of the Seventh International Natural Language Generation Conference

2009

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Le projet BabyTalk : génération de texte à partir de données hétérogènes pour la prise de décision en unité néonatale
François Portet | Albert Gatt | Jim Hunter | Ehud Reiter | Somayajulu Sripada
Actes de la 16ème conférence sur le Traitement Automatique des Langues Naturelles. Articles longs

Notre société génère une masse d’information toujours croissante, que ce soit en médecine, en météorologie, etc. La méthode la plus employée pour analyser ces données est de les résumer sous forme graphique. Cependant, il a été démontré qu’un résumé textuel est aussi un mode de présentation efficace. L’objectif du prototype BT-45, développé dans le cadre du projet Babytalk, est de générer des résumés de 45 minutes de signaux physiologiques continus et d’événements temporels discrets en unité néonatale de soins intensifs (NICU). L’article présente l’aspect génération de texte de ce prototype. Une expérimentation clinique a montré que les résumés humains améliorent la prise de décision par rapport à l’approche graphique, tandis que les textes de BT-45 donnent des résultats similaires à l’approche graphique. Une analyse a identifié certaines des limitations de BT-45 mais en dépit de cellesci, notre travail montre qu’il est possible de produire automatiquement des résumés textuels efficaces de données complexes.

2008

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Using Spatial Reference Frames to Generate Grounded Textual Summaries of Georeferenced Data
Ross Turner | Somayajulu Sripada | Ehud Reiter | Ian Davy
Proceedings of the Fifth International Natural Language Generation Conference

2007

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Atlas.txt: Linking Geo-referenced Data to Text for NLG
Kavita Thomas | Somayajulu Sripada
Proceedings of the Eleventh European Workshop on Natural Language Generation (ENLG 07)

2006

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Generating Spatio-Temporal Descriptions in Pollen Forecasts
Ross Turner | Somayajulu Sripada | Ehud Reiter | Ian P Davy
Demonstrations

2005

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Evaluation of an NLG System using Post-Edit Data: Lessons Learnt
Somayajulu Sripada | Ehud Reiter | Lezan Hawizy
Proceedings of the Tenth European Workshop on Natural Language Generation (ENLG-05)

2003

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Summarizing Neonatal Time Series Data
Somayajulu G. Sripada | Ehud Reiter | Jim Hunter | Jin Yu
10th Conference of the European Chapter of the Association for Computational Linguistics

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Learning the Meaning and Usage of Time Phrases from a Parallel Text-Data Corpus
Ehud Reiter | Somayajulu Sripada
Proceedings of the HLT-NAACL 2003 Workshop on Learning Word Meaning from Non-Linguistic Data

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Acquiring and Using Limited User Models in NLG
Ehud Reiter | Somayajulu Sripada | Sandra Williams
Proceedings of the 9th European Workshop on Natural Language Generation (ENLG-2003) at EACL 2003

2002

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Should Corpora Texts Be Gold Standards for NLG?
Ehud Reiter | Somayajulu Sripada
Proceedings of the International Natural Language Generation Conference

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Squibs and Discussions: Human Variation and Lexical Choice
Ehud Reiter | Somayajulu Sripada
Computational Linguistics, Volume 28, Number 4, December 2002

2001

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A Two-Staged Model For Content Determination
Somayajula G. Sripada | Ehud Reiter | Jim Hunter | Jin Yu
Proceedings of the ACL 2001 Eighth European Workshop on Natural Language Generation (EWNLG)