Results 61 to 70 of about 679,813 (367)
Dialog State Tracking: A Neural Reading Comprehension Approach [PDF]
SIGDIAL Conferences, 2019 Dialog state tracking is used to estimate the current belief state of a dialog given all the preceding conversation. Machine reading comprehension, on the other hand, focuses on building systems that read passages of text and answer questions that ...
Shuyang Gao +4 more
semanticscholar +1 more source
VD-BERT: A Unified Vision and Dialog Transformer with BERT [PDF]
Conference on Empirical Methods in Natural Language Processing, 2020 Visual dialog is a challenging vision-language task, where a dialog agent needs to answer a series of questions through reasoning on the image content and dialog history.
Yue Wang +5 more
semanticscholar +1 more source
Nordic Journal of Art and Research, 2015 Denne artikkelen bygger på studien «Skapelsen av et etnodrama» som omhandler skapelsesprosessen av et manuskript basert på intervju av unge skeive voksne. Med en hermeneutisk-fenomenologisk kunnskapsforståelse tar forskeren utgangspunkt i det kvalitative forskningsintervjuet og fortolkning av den subjektive livsverdenen som materiale for skapelsen av ...
openaire +4 more sources
ANALISIS KALIMAT DIALOG DALAM NASKAH DRAMA �PADA SUATU HARI� KARYA ARIFIN C. NOER
Fon, 2017 Judul penelitian ini adalah Analisis Kalimat Dialog dalam Naskah Drama Pada Suatu Hari Karya Arifin C. Noer (Sebuah Analisis Pragmatik tentang Deiksis dan Praanggapan).
Ida Hamidah, Hesti Angreaningsih
doaj +1 more source
Optimizing human-interpretable dialog management policy using Genetic Algorithm
, 2015 Automatic optimization of spoken dialog management policies that are robust to environmental noise has long been the goal for both academia and industry. Approaches based on reinforcement learning have been proved to be effective.
Ren, Hang, Xu, Weiqun, Yan, Yonghong
core +1 more source
Hybrid Code Networks: practical and efficient end-to-end dialog control with supervised and reinforcement learning [PDF]
Annual Meeting of the Association for Computational Linguistics, 2017 End-to-end learning of recurrent neural networks (RNNs) is an attractive solution for dialog systems; however, current techniques are data-intensive and require thousands of dialogs to learn simple behaviors.
J. Williams, Kavosh Asadi, G. Zweig
semanticscholar +1 more source
Parent‐to‐Child Information Disclosure in Pediatric Oncology
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Despite professional consensus regarding the importance of open communication with pediatric cancer patients about their disease, actual practice patterns of disclosure are understudied. Extant literature suggests a significant proportion of children are not told about their diagnosis/prognosis, which is purported to negatively ...
Rachel A. Kentor +12 more
wiley +1 more source
Incremental LSTM-based Dialog State Tracker
, 2015 A dialog state tracker is an important component in modern spoken dialog systems. We present an incremental dialog state tracker, based on LSTM networks. It directly uses automatic speech recognition hypotheses to track the state. We also present the key
Jurcicek, Filip, Zilka, Lukas
core +1 more source
Semantic Parsing for Task Oriented Dialog using Hierarchical Representations [PDF]
Conference on Empirical Methods in Natural Language Processing, 2018 Task oriented dialog systems typically first parse user utterances to semantic frames comprised of intents and slots. Previous work on task oriented intent and slot-filling work has been restricted to one intent per query and one slot label per token ...
S. Gupta +4 more
semanticscholar +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Psychological safety (PS) is essential for teamwork, communication, and patient safety in complex healthcare environments. In pediatric oncology, interprofessional collaboration occurs under high emotional and organizational demands. Low PS may increase stress, burnout, and adverse events.
Alexandros Rahn +4 more
wiley +1 more source