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Smart Auto-completion in Live Chat Utilizing the Power of T5 ; Smart automatisk komplettering i livechatt som utnyttjar styrkan hos T5
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Wang, Zhanpeng. - : KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021
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Sequence-to-Sequence Acoustic Modeling with Semi-Stepwise Monotonic Attention for Speech Synthesis
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In: Applied Sciences ; Volume 11 ; Issue 21 (2021)
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Improving Grapheme-to-Phoneme Conversion for Anglicisms in German Speech Recognition
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In: Fraunhofer IAIS (2021)
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Next-gen sequencing identifies non-coding variation disrupting miRNA-binding sites in neurological disorders
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| 5 |
Asm2Seq: Explainable Assembly Code Functional Summary Generation
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The Rare Word Issue in Natural Language Generation: A Character-Based Solution
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Abstract:
In this paper, we analyze the problem of generating fluent English utterances from tabular data, focusing on the development of a sequence-to-sequence neural model which shows two major features: the ability to read and generate character-wise, and the ability to switch between generating and copying characters from the input: an essential feature when inputs contain rare words like proper names, telephone numbers, or foreign words. Working with characters instead of words is a challenge that can bring problems such as increasing the difficulty of the training phase and a bigger error probability during inference. Nevertheless, our work shows that these issues can be solved and efforts are repaid by the creation of a fully end-to-end system, whose inputs and outputs are not constrained to be part of a predefined vocabulary, like in word-based models. Furthermore, our copying technique is integrated with an innovative shift mechanism, which enhances the ability to produce outputs directly from inputs. We assess performance on the E2E dataset, the benchmark used for the E2E NLG challenge, and on a modified version of it, created to highlight the rare word copying capabilities of our model. The results demonstrate clear improvements over the baseline and promising performance compared to recent techniques in the literature.
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Keyword:
data-to-text generation; deep learning; natural language processing; sequence-to-sequence models
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URL: http://hdl.handle.net/2318/1787979
https://doi.org/10.3390/informatics8010020
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| 7 |
Controllable Sentence Simplification
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In: LREC 2020 - 12th Language Resources and Evaluation Conference ; https://hal.inria.fr/hal-02678214 ; LREC 2020 - 12th Language Resources and Evaluation Conference, May 2020, Marseille, France ; http://www.lrec-conf.org/proceedings/lrec2020/index.html (2020)
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| 8 |
Investigating Language Impact in Bilingual Approaches for Computational Language Documentation
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In: Proceedings of the 1st Joint SLTU and CCURL Workshop (SLTU-CCURL 2020), ; SLTU-CCURL workshop, LREC 2020 ; https://hal.archives-ouvertes.fr/hal-02895907 ; SLTU-CCURL workshop, LREC 2020, May 2020, Marseille, France (2020)
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| 9 |
Tamil Paraphrase Detection Using Encoder-Decoder Neural Networks
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In: IFIP Advances in Information and Communication Technology ; 3rd International Conference on Computational Intelligence in Data Science (ICCIDS) ; https://hal.inria.fr/hal-03434784 ; 3rd International Conference on Computational Intelligence in Data Science (ICCIDS), Feb 2020, Chennai, India. pp.30-42, ⟨10.1007/978-3-030-63467-4_3⟩ (2020)
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| 10 |
A Data-Efficient End-to-End Spoken Language Understanding Architecture
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In: International Conference on Acoustics, Speech, and Signal Processing (ICASSP) ; https://hal.archives-ouvertes.fr/hal-03094850 ; International Conference on Acoustics, Speech, and Signal Processing (ICASSP), May 2020, Barcellone, Spain (2020)
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| 11 |
Comparison of Word2vec with Hash2vec for Machine Translation
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In: Master's Projects (2020)
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| 12 |
Advances in deep learning methods for speech recognition and understanding
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| 13 |
Interpreting Sequence-to-Sequence Models for Russian Inflectional Morphology
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In: Proceedings of the Society for Computation in Linguistics (2020)
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| 14 |
Empirical Evaluation of Sequence-to-Sequence Models for Word Discovery in Low-resource Settings
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In: Interspeech 2019 ; https://hal.archives-ouvertes.fr/hal-02193867 ; Interspeech 2019, Sep 2019, Graz, Austria (2019)
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| 15 |
SEQUENCE-TO-SEQUENCE MODELLING OF F0 FOR SPEECH EMOTION CONVERSION
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In: IEEE International Conference on Acoustics, Speech, and Signal Processing ; https://hal.sorbonne-universite.fr/hal-02018439 ; IEEE International Conference on Acoustics, Speech, and Signal Processing, May 2019, Brighton, United Kingdom (2019)
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| 16 |
Abstractive Sentence Compression with Event Attention
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In: Applied Sciences ; Volume 9 ; Issue 19 (2019)
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| 17 |
Diverse Decoding for Abstractive Document Summarization
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In: Applied Sciences ; Volume 9 ; Issue 3 (2019)
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| 18 |
Neural Sign Language Translation Based on Human Keypoint Estimation
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In: Applied Sciences ; Volume 9 ; Issue 13 (2019)
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Data quality in the deep learning era: Active semi-supervised learning and text normalization for natural language understanding
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