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Neural Speech Completion

Kazuki Tsunematsu, Johanes Effendi, Sakriani Sakti, Satoshi Nakamura
2020 Interspeech 2020  
This paper proposes a speech completion system based on deep learning and discusses the construction in a text-totext, speech-to-text, and speech-to-speech framework.  ...  We evaluate our system on domain-specific sentences with synthesized speech utterances that are only 25%, 50%, or 75% complete.  ...  Speech-to-text completion Next, we investigated the performance of our speech-to-text system on sentence completion.  ... 
doi:10.21437/interspeech.2020-2110 dblp:conf/interspeech/TsunematsuES020 fatcat:2jbfivxfcjh6jh34v3t3ttxwki

N-gram models for Text Generation in Hindi Language

Tejashree Ghude, Roshni Chauhan, Krushna Dahake, Atharv Bhosale, Tushar Ghorpade, M.D. Patil, V.A. Vyawahare
2022 ITM Web of Conferences  
Hence, to make User Experience more effective while interacting with Software Applications, we aim to build a Model using Natural Language Processing which takes a specific word as an input and predicts  ...  the subsequent words for completing the sentence.It will act as a tab- complete function in Hindi language.  ...  Fig 4 . 3 43 Fig 4.3 Sentence generation Using these N-grams and the probabilities of the occurrences of certain words in certain sequences could improve the predictions of auto completion systems.  ... 
doi:10.1051/itmconf/20224403062 fatcat:m6qhjk76azc7nbqiiza6gfjk6e

On-Device detection of sentence completion for voice assistants with low-memory footprint

Rahul Kumar, Vijeta Gour, Chandan Pandey, Godawari Sudhakar Rao, Priyadarshini Pai, Anmol Bhasin, Ranjan Samal
2020 International Conference on Natural Language Processing  
Conventional approaches for SCD operate within the confines of sentence boundary detection using language models or sentence end detection using speech and text features.  ...  Sentence completion detection (SCD) is an important task for various downstream Natural Language Processing (NLP) based applications.  ...  These systems rely on the text, predicted by a streaming speech recognition (ASR) system. Streaming ASR produces text continuously.  ... 
dblp:conf/icon-nlp/KumarGPRPBS20 fatcat:rk3mqbysgfe4hlyjuk2gqtju6u

Architecture of a Web-based Predictive Editor for Controlled Natural Language Processing [article]

Stephen Guy, Rolf Schwitter
2014 arXiv   pre-print
The text editor can display multiple sets of lookahead categories simultaneously for different possible sentence completions, anaphoric expressions, and supports the addition of new content words to the  ...  In this paper, we describe the architecture of a web-based predictive text editor being developed for the controlled natural language PENG^ASP).  ...  Lookahead categories for the available sentence completion are highlighted using the pull-down menus.  ... 
arXiv:1408.0016v1 fatcat:ueotmqx6uraalh772gbys63o5u

Computational Linguistics: Text Prediction and Sentence Correction

Padmalatha E, Sailekya S
2020 Helix  
Versions after versions of popular text editors have come, and yet no editor has addressed the difficulty of predicting the next possible word and correction of predicted sentence.  ...  This in proposed method it explores the use of a new software for the input on desktops, which relies on a dynamic predictive algorithm using n-grams and suffix trees to significantly reduce the effort  ...  Spell Check Sentence Correction Final Output The complete text prediction is explained in the following Figure7.  ... 
doi:10.29042/2020-10-4-06-12 fatcat:u4tjhh5kfnfb7c4x4cuxmxtwte

SemantiKLUE: Robust Semantic Similarity at Multiple Levels Using Maximum Weight Matching

Thomas Proisl, Stefan Evert, Paul Greiner, Besim Kabashi
2014 Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014)  
At the core of the system is a word-to-word alignment of two texts using a maximum weight matching algorithm.  ...  Being able to quantify the semantic similarity between two texts is important for many practical applications.  ...  Conclusion SemantiKLUE is a robust system for predicting the semantic similarity between two texts that can also be used to predict entailment.  ... 
doi:10.3115/v1/s14-2093 dblp:conf/semeval/ProislEGK14 fatcat:zbzihwseqvh2dos55n6srihbpi

A Design Engineering Approach for Quantitatively Exploring Context-Aware Sentence Retrieval for Nonspeaking Individuals with Motor Disabilities

Per Ola Kristensson, James Lilley, Rolf Black, Annalu Waller
2020 Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems  
accuracy of the underlying auto-complete word prediction algorithm and the accuracy of sensed context information under varying assumptions.  ...  We then study the theoretical performance envelopes of a context-aware sentence retrieval system, identifying potential keystroke savings as a function of the parameters of the subsystems, such as the  ...  When the user has typed a word, phrase or sentence the user can speak the text using speech synthesis.  ... 
doi:10.1145/3313831.3376525 dblp:conf/chi/KristenssonLBW20 fatcat:2w2r3bdrtvgchbgto6vw25mbum

Sentence Completion using NLP Techniques

Umang Rupareliya
2019 International Journal for Research in Applied Science and Engineering Technology  
The tasks involve training on a large corpus of unannotated text, to then try to predict the missing words in the test set which contains thousands of sentences where one word is missing and five alternatives  ...  Methods using local information and global information for the task of sentence completion are used and we find that method using global information (Latent Semantic Analysis) proves to be better than  ...  We would like to extend our heartfelt gratitude to our mentor Prof Nirmala Shinde for guiding us throughout our project work.  ... 
doi:10.22214/ijraset.2019.4474 fatcat:hslskodrf5dppagxj44kk6ynma

Modelling text prediction systems in low- and high-inflected languages

Nestor Garay-Vitoria, Julio Abascal
2010 Computer Speech and Language  
In order to discuss general issues of text prediction it is necessary to propose abstract descriptions of the methods used. In this paper a number of models applied to text prediction are presented.  ...  Text prediction was initially proposed to help people with a low text composition speed to enhance their message composition.  ...  Models of text prediction systems in a high-inflected language Word prediction using frequencies As was mentioned in subsection 2.1, word prediction using frequencies is language independent.  ... 
doi:10.1016/j.csl.2009.03.008 fatcat:ncpmcpd43nczxa2rvw5iccmgru

TransAhead: A Computer-Assisted Translation and Writing Tool

Chung-Chi Huang, Ping-Che Yang, Keh-Jiann Chen, Jason S. Chang
2012 North American Chapter of the Association for Computational Linguistics  
We introduce a method for learning to predict text completion given a source text and partial translation.  ...  In our approach, predictions are offered aimed at alleviating users' burden on lexical and grammar choices, and improving productivity.  ...  Summary We have introduced a method for learning to offer grammar and text predictions expected to assist the user in translation and writing. We have implemented and evaluated the method.  ... 
dblp:conf/naacl/HuangYCC12 fatcat:3qrmj6a7wfd5jbityux4d6kpyq

Closing the loop: from paper to protein annotation using supervised Gene Ontology classification

J. Gobeill, E. Pasche, D. Vishnyakova, P. Ruch
2014 Database: The Journal of Biological Databases and Curation  
Thanks to BioCreative IV, we were able to design a complete workflow for curation: given a gene name and a full text, this system is able to select evidence sentences for curation and to deliver highly  ...  The subtask A consisted in selecting GO evidence sentences for a relevant gene in a full text.  ...  In GOCat4FT, the user has to input a gene name and a full text (or a PMC identifier), and the system will display evidence sentences for GO curation (subtask A), and GO concepts provided by GOCat (subtask  ... 
doi:10.1093/database/bau088 pmid:25190367 pmcid:PMC4154439 fatcat:thufceqbqndipee5owc4vydwjy

Introduction to the CoNLL-2001 Shared Task: Clause Identification [article]

Erik F. Tjong Kim Sang, Herve Dejean
2001 arXiv   pre-print
We describe the CoNLL-2001 shared task: dividing text into clauses.  ...  We give background information on the data sets, present a general overview of the systems that have taken part in the shared task and briefly discuss their performance.  ...  Acknowledgements We would like to thank SIGNLL for giving us the opportunity to organize this shared task and our colleagues of the Seminar für Sprachwissenschaft in Tübingen, CNTS -Language Technology  ... 
arXiv:cs/0107016v1 fatcat:fqa7qdirs5ftpeyeifuozco7l4

Predicting Reading Comprehension Scores of Elementary School Students

Yuyang Nie, Helene Deacon, Alona Fyshe, Carrie Demmans Epp, Antonija Mitrovic, Nigel Bosch
2022 Zenodo  
This provides insight into how different characteristics of the text and questions can be used to predict student performance, leading to new ideas about how text and reading comprehension interact.  ...  In this study, we examined the impact of word and sentence level text-features on children's reading comprehension.  ...  Rare Word Use The number of rare words in a text influences reading comprehension; one rare word can lead to a complete miscomprehension of a sentence [23] .  ... 
doi:10.5281/zenodo.6852952 fatcat:r5pm7fxvtbg33galkoysq44iye

Learning to Complete Sentences [chapter]

Steffen Bickel, Peter Haider, Tobias Scheffer
2005 Lecture Notes in Computer Science  
We consider the problem of predicting how a user will continue a given initial text fragment.  ...  Intuitively, our goal is to develop a "tab-complete" function for natural language, based on a model that is learned from text data.  ...  Instance-based Sentence Completion An alternative to N -gram models is to retrieve, from the training collection, the sentence that starts most similarly, and use its remainder as a completion hypothesis  ... 
doi:10.1007/11564096_47 fatcat:lyfgcrdjlvg5doiqzs3qcojage

Effidit: Your AI Writing Assistant [article]

Shuming Shi, Enbo Zhao, Duyu Tang, Yan Wang, Piji Li, Wei Bi, Haiyun Jiang, Guoping Huang, Leyang Cui, Xinting Huang, Cong Zhou, Yong Dai (+1 others)
2022 arXiv   pre-print
In the text completion category, Effidit supports generation-based sentence completion, retrieval-based sentence completion, and phrase completion.  ...  With the emergence of large-scale neural language models, some systems support automatically completing a sentence or a paragraph.  ...  Major functions of Effidit are summarized below, • Text completion: In this category, Effidit supports generation-based sentence completion, retrieval-based sentence completion, and phrase completion,  ... 
arXiv:2208.01815v2 fatcat:toqqcda4cngfldicifpk5kw4ju
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