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1
Emotional Speech Recognition Using Deep Neural Networks
In: ISSN: 1424-8220 ; Sensors ; https://hal.archives-ouvertes.fr/hal-03632853 ; Sensors, MDPI, 2022, 22 (4), pp.1414. ⟨10.3390/s22041414⟩ (2022)
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2
Prosodic Feature-Based Discriminatively Trained Low Resource Speech Recognition System
In: Sustainability; Volume 14; Issue 2; Pages: 614 (2022)
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3
Text Data Augmentation for the Korean Language
In: Applied Sciences; Volume 12; Issue 7; Pages: 3425 (2022)
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4
Emotional Speech Recognition Using Deep Neural Networks
In: Sensors; Volume 22; Issue 4; Pages: 1414 (2022)
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5
A Study of Data Augmentation for ASR Robustness in Low Bit Rate Contact Center Recordings Including Packet Losses
In: Applied Sciences; Volume 12; Issue 3; Pages: 1580 (2022)
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6
Modeling the effect of military oxygen masks on speech characteristics
In: Interspeech 2021 ; https://hal.archives-ouvertes.fr/hal-03325087 ; Interspeech 2021, Aug 2021, Brno, Czech Republic (2021)
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7
Simulating reading mistakes for child speech Transformer-based phone recognition
In: Annual Conference of the International Speech Communication Association (INTERSPEECH) ; https://hal.archives-ouvertes.fr/hal-03257870 ; Annual Conference of the International Speech Communication Association (INTERSPEECH), Aug 2021, Brno, Czech Republic (2021)
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8
A Data Augmentation Approach for Sign-Language-To-Text Translation In-The-Wild ...
Nunnari, Fabrizio; España-Bonet, Cristina; Avramidis, Eleftherios. - : Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2021
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9
Effekten av textaugmenteringsstrategier på träffsäkerhet, F1-värde och viktat F1-värde ; The effect of text data augmentation strategies on Accuracy, F1-score, and weighted F1-score
Shmas, George; Svedberg, Jonatan. - : KTH, Hälsoinformatik och logistik, 2021
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10
Using Data Augmentation and Time-Scale Modification to Improve ASR of Children’s Speech in Noisy Environments
In: Applied Sciences ; Volume 11 ; Issue 18 (2021)
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11
Generating Synthetic Disguised Faces with Cycle-Consistency Loss and an Automated Filtering Algorithm
In: Mathematics; Volume 10; Issue 1; Pages: 4 (2021)
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12
Volumetric changes at implant sites: A systematic appraisal of traditional methods and optical scanning- based digital technologies
Tavelli, Lorenzo; Barootchi, Shayan; Majzoub, Jad. - : Wiley Periodicals, Inc., 2021
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13
Rethinking Data Augmentation for Low-Resource Neural Machine Translation: A Multi-Task Learning Approach
Sánchez-Cartagena, Víctor M.; Sánchez-Martínez, Felipe; Pérez-Ortiz, Juan Antonio. - : Association for Computational Linguistics, 2021
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14
Improving Short Text Classification Through Global Augmentation Methods
In: Lecture Notes in Computer Science ; 4th International Cross-Domain Conference for Machine Learning and Knowledge Extraction (CD-MAKE) ; https://hal.inria.fr/hal-03414750 ; 4th International Cross-Domain Conference for Machine Learning and Knowledge Extraction (CD-MAKE), Aug 2020, Dublin, Ireland. pp.385-399, ⟨10.1007/978-3-030-57321-8_21⟩ (2020)
Abstract: International audience ; We study the effect of different approaches to text augmentation. To do this we use three datasets that include social media and formal text in the form of news articles. Our goal is to provide insights for practitioners and researchers on making choices for augmentation for classification use cases. We observe that Word2Vec-based augmentation is a viable option when one does not have access to a formal synonym model (like WordNet-based augmentation). The use of mixup further improves performance of all text based augmentations and reduces the effects of overfitting on a tested deep learning model. Round-trip translation with a translation service proves to be harder to use due to cost and as such is less accessible for both normal and low resource use-cases.
Keyword: [INFO]Computer Science [cs]; [SHS.INFO]Humanities and Social Sciences/Library and information sciences; Data augmentation; Deep Neural Networks; Natural Language Processing; Text classification
URL: https://hal.inria.fr/hal-03414750/file/497121_1_En_21_Chapter.pdf
https://hal.inria.fr/hal-03414750
https://doi.org/10.1007/978-3-030-57321-8_21
https://hal.inria.fr/hal-03414750/document
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15
Data Augmenting Contrastive Learning of Speech Representations in the Time Domain
In: SLT 2020 - IEEE Spoken Language Technology Workshop ; https://hal.archives-ouvertes.fr/hal-03070321 ; SLT 2020 - IEEE Spoken Language Technology Workshop, Dec 2020, Shenzhen / Virtual, China (2020)
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16
Characterization and classification of semantic image-text relations ...
Otto, Christian; Springstein, Matthias; Anand, Avishek. - : London : Springer, 2020
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17
Characterization and classification of semantic image-text relations ...
Otto, C.; Springstein, M.; Anand, A.. - : Berlin : Springer Nature, 2020
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18
Using Complexity-Identical Human- and Machine-Directed Utterances to Investigate Addressee Detection for Spoken Dialogue Systems
In: Sensors ; Volume 20 ; Issue 9 (2020)
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19
NAT: Noise-Aware Training for Robust Neural Sequence Labeling
In: Fraunhofer IAIS (2020)
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20
MonaLog: a Lightweight System for Natural Language Inference Based on Monotonicity
In: Proceedings of the Society for Computation in Linguistics (2020)
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