Results 31 to 40 of about 2,639,905 (339)
An Efficient Deep Learning for Thai Sentiment Analysis
Data, 2023 The number of reviews from customers on travel websites and platforms is quickly increasing. They provide people with the ability to write reviews about their experience with respect to service quality, location, room, and cleanliness, thereby helping ...
Nattawat Khamphakdee +1 more
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A large annotated corpus for learning natural language inference [PDF]
Conference on Empirical Methods in Natural Language Processing, 2015 Understanding entailment and contradiction is fundamental to understanding natural language, and inference about entailment and contradiction is a valuable testing ground for the development of semantic representations. However, machine learning research
Samuel R. Bowman +3 more
semanticscholar +1 more source
Applied Sciences, 2020 The modeling of fundamental frequency (F0) in speech synthesis is a critical factor affecting the intelligibility and naturalness of synthesized speech. In this paper, we focus on improving the modeling of F0 for Isarn speech synthesis. We propose the F0
Pongsathon Janyoi, Pusadee Seresangtakul
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A Survey of the Usages of Deep Learning for Natural Language Processing
IEEE Transactions on Neural Networks and Learning Systems, 2020 Over the last several years, the field of natural language processing has been propelled forward by an explosion in the use of deep learning models.
Dan Otter, Julian R. Medina, J. Kalita
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Literature Review of Qualitative Data with Natural Language Processing
Journal of Robotics Spectrum, 2023 Qualitative research techniques are frequently employed by scholars in the field of social sciences when investigating communities and their communication media.
Bukuroshe Elira Epoka
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A Method of Chinese-Vietnamese Bilingual Corpus Construction for Machine Translation
IEEE Access, 2022 A bilingual corpus is vital for natural language processing problems, especially in machine translation. The larger and better quality the corpus is, the higher the efficiency of the resulting machine translation is.
Phuoc Tran +4 more
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COVID-Twitter-BERT: A natural language processing model to analyse COVID-19 content on Twitter [PDF]
Frontiers in Artificial Intelligence, 2020 Introduction This study presents COVID-Twitter-BERT (CT-BERT), a transformer-based model that is pre-trained on a large corpus of COVID-19 related Twitter messages. CT-BERT is specifically designed to be used on COVID-19 content, particularly from social
Martin Müller +2 more
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A Systematic Comparison of Data Selection Criteria for SMT Domain Adaptation
The Scientific World Journal, 2014 Data selection has shown significant improvements in effective use of training data by extracting sentences from large general-domain corpora to adapt statistical machine translation (SMT) systems to in-domain data.
Longyue Wang +4 more
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Chemical-induced disease relation extraction via attention-based distant supervision
BMC Bioinformatics, 2019 Background Automatically understanding chemical-disease relations (CDRs) is crucial in various areas of biomedical research and health care. Supervised machine learning provides a feasible solution to automatically extract relations between biomedical ...
Jinghang Gu +3 more
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Speech Rate Adjustments in Conversations With an Amazon Alexa Socialbot
Frontiers in Communication, 2021 This paper investigates users’ speech rate adjustments during conversations with an Amazon Alexa socialbot in response to situational (in-lab vs. at-home) and communicative (ASR comprehension errors) factors.
Michelle Cohn +7 more
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