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Emotional Speech Recognition Using Deep Neural Networks
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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
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In: Sustainability; Volume 14; Issue 2; Pages: 614 (2022)
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| 3 |
Text Data Augmentation for the Korean Language
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In: Applied Sciences; Volume 12; Issue 7; Pages: 3425 (2022)
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| 4 |
Emotional Speech Recognition Using Deep Neural Networks
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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
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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
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In: Interspeech 2021 ; https://hal.archives-ouvertes.fr/hal-03325087 ; Interspeech 2021, Aug 2021, Brno, Czech Republic (2021)
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Abstract:
International audience ; Wearing an oxygen mask changes the speech production of speakers. It indeed modifies the vocal apparatus and perturbs the articulatory movements of the speaker. This paper studies the impact of the oxygen mask of military aircraft pilots on formant trajectories, both dynamically (variations of the formants at a utterance level) and globally (mean value at the utterance level) for 12 speakers. A comparative analysis of speech collected with and without an oxygen mask shows that the mask has a significant impact on the formant trajectories, both on the mean values and on the formant variations at the utterance level. This impact is strongly dependent on the speaker and also on the mask model. These observations suggest that the articulatory movements of the speaker are modified by the presence of the mask. These observations are validated via a preliminary ASR experiment that uses a data augmentation technique based on articulatory perturbations that are driven by our experimental observations.
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Keyword:
[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing; articulatory perturbation; data augmentation; oxygen mask; speech variation
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URL: https://hal.archives-ouvertes.fr/hal-03325087
https://hal.archives-ouvertes.fr/hal-03325087/file/paper.pdf
https://hal.archives-ouvertes.fr/hal-03325087/document
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| 7 |
Simulating reading mistakes for child speech Transformer-based phone recognition
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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 ...
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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
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| 10 |
Using Data Augmentation and Time-Scale Modification to Improve ASR of Children’s Speech in Noisy Environments
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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
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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
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Rethinking Data Augmentation for Low-Resource Neural Machine Translation: A Multi-Task Learning Approach
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| 14 |
Improving Short Text Classification Through Global Augmentation Methods
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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)
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| 15 |
Data Augmenting Contrastive Learning of Speech Representations in the Time Domain
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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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Characterization and classification of semantic image-text relations ...
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| 17 |
Characterization and classification of semantic image-text relations ...
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| 18 |
Using Complexity-Identical Human- and Machine-Directed Utterances to Investigate Addressee Detection for Spoken Dialogue Systems
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In: Sensors ; Volume 20 ; Issue 9 (2020)
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| 19 |
NAT: Noise-Aware Training for Robust Neural Sequence Labeling
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In: Fraunhofer IAIS (2020)
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| 20 |
MonaLog: a Lightweight System for Natural Language Inference Based on Monotonicity
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In: Proceedings of the Society for Computation in Linguistics (2020)
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