Results 1 to 10 of about 1,627,644 (339)
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
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source
ScispaCy: Fast and Robust Models for Biomedical Natural Language Processing [PDF]
BioNLP@ACL, 2019 Despite recent advances in natural language processing, many statistical models for processing text perform extremely poorly under domain shift. Processing biomedical and clinical text is a critically important application area of natural language ...
Mark Neumann +3 more
semanticscholar +1 more source
The Scientific World Journal, 2014 With the rapid development of machine translation (MT), the MT evaluation becomes very important to timely tell us whether the MT system makes any progress.
Aaron L.-F. Han +4 more
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source
Improving Transformer-Based Neural Machine Translation with Prior Alignments
Complexity, 2021 Transformer is a neural machine translation model which revolutionizes machine translation. Compared with traditional statistical machine translation models and other neural machine translation models, the recently proposed transformer model radically ...
Thien Nguyen +3 more
doaj +1 more source
Enhancing Conversational Model With Deep Reinforcement Learning and Adversarial Learning
IEEE Access, 2023 This paper develops a Chatbot conversational model that is aimed to achieve two goals: 1) utilizing contextual information to generate accurate and relevant responses, and 2) implementing strategies to make conversations human-like.
Quoc-Dai Luong Tran +2 more
doaj +1 more source
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