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Improved Spoken Language Representation for Intent Understanding in a Task-Oriented Dialogue System
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In: Sensors; Volume 22; Issue 4; Pages: 1509 (2022)
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Abstract:
Successful applications of deep learning technologies in the natural language processing domain have improved text-based intent classifications. However, in practical spoken dialogue applications, the users’ articulation styles and background noises cause automatic speech recognition (ASR) errors, and these may lead language models to misclassify users’ intents. To overcome the limited performance of the intent classification task in the spoken dialogue system, we propose a novel approach that jointly uses both recognized text obtained by the ASR model and a given labeled text. In the evaluation phase, only the fine-tuned recognized language model (RLM) is used. The experimental results show that the proposed scheme is effective at classifying intents in the spoken dialogue system containing ASR errors.
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Keyword:
intent understanding; speech recognition; spoken dialogue system; spoken language modeling; task-oriented dialogue system
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URL: https://doi.org/10.3390/s22041509
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| 2 |
A Literature Survey of Recent Advances in Chatbots
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In: Information; Volume 13; Issue 1; Pages: 41 (2022)
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Solomon Marcus: pledoarie pentru "Dialogul disciplinelor" ...
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Solomon Marcus: pledoarie pentru "Dialogul disciplinelor" ...
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| 5 |
Recent Advances in Dialogue Machine Translation
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In: Information ; Volume 12 ; Issue 11 (2021)
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Designing a virtual patient dialogue system based on terminology-rich resources: Challenges and evaluation
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Multimodal and Interactive Models for Visually Grounded Language Learning ; Développement de modèles multimodaux intéractifs pour l'apprentissage du language dans des environnements visuels
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In: https://tel.archives-ouvertes.fr/tel-03018038 ; Neural and Evolutionary Computing [cs.NE]. Université de Lille; École doctorale, ED SPI 074 : Sciences pour l'Ingénieur, 2020. English (2020)
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Spot The Bot : a robust and efficient framework for the evaluation of conversational dialogue systems ...
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Languages in a network-centric world ; Языки в сетецентрическом мире. ; Мова в мережецентричному світі
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In: Bionics of Intelligence; Vol. 1 No. 94 (2020): Scientific and Technical Journal "Bionics of Intelligence"; 3-6 ; Бионика интеллекта; Том 1 № 94 (2020): Научно-технический журнал "Бионика интеллекта"; 3-6 ; Біоніка інтелекту; Том 1 № 94 (2020): Науково-технічний журнал "Біоніка інтелекту"; 3-6 ; 2663-306X ; 2663-3051 (2020)
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| 11 |
Designing a virtual patient dialogue system based on terminology-rich resources: challenges and evaluation
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In: ISSN: 1351-3249 ; EISSN: 1469-8110 ; Natural Language Engineering ; https://hal.archives-ouvertes.fr/hal-02358021 ; Natural Language Engineering, Cambridge University Press (CUP), 2019, pp.1-38 (2019)
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| 13 |
Using Alignments in Automatic Paraphrase Production to Combat Data Sparsity in Question Interpretation for a Virtual Patient Dialogue System
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| 14 |
Usage-based Learning in Human Interaction with an Adpative Assistant Agent ; Apprentissage basé sur l’usage en interaction humaine avec un assistant adaptatif
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Speech and language resources for the development of dialogue systems and problems arising from their deployment
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On-Talk and Off-Talk Detection: A Discrete Wavelet Transform Analysis of Electroencephalogram ; 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2018)
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Interactive Question Answering Using Frame-Based Knowledge Representation
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Natural language generation for spoken dialogue system using RNN encoder-decoder networks
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| 20 |
Dialoogsüsteem ja läbirääkimiste struktuur
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In: Eesti Rakenduslingvistika Ühingu Aastaraamat, Vol 13, Pp 37-51 (2017) (2017)
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