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Using Automatic Speech Recognition to Optimize Hearing-Aid Time Constants
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In: ISSN: 1662-4548 ; EISSN: 1662-453X ; Frontiers in Neuroscience ; https://hal.archives-ouvertes.fr/hal-03627441 ; Frontiers in Neuroscience, Frontiers, 2022, 16 (779062), ⟨10.3389/fnins.2022.779062⟩ ; https://www.frontiersin.org/articles/10.3389/fnins.2022.779062/full (2022)
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A fine-grained recognition of Named Entities in ELTeC collection using cascades
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In: Final Action Event of COST Action Distant Reading for European Literary History ; https://hal.archives-ouvertes.fr/hal-03615219 ; Final Action Event of COST Action Distant Reading for European Literary History, Christof Schöch, Apr 2022, Krakow, Poland ; https://www.distant-reading.net/events/conference-programme/ (2022)
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RETRIEVING SPEAKER INFORMATION FROM PERSONALIZED ACOUSTIC MODELS FOR SPEECH RECOGNITION
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In: IEEE ICASSP 2022 ; https://hal.archives-ouvertes.fr/hal-03539741 ; IEEE ICASSP 2022, 2022, Singapour, Singapore (2022)
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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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Abstract:
International audience ; The expression of emotions in human communication plays a very important role in the information that needs to be conveyed to the partner. The forms of expression of human emotions are very rich. It could be body language, facial expressions, eye contact, laughter, and tone of voice. The languages of the world’s peoples are different, but even without understanding a language in communication, people can almost understand part of the message that the other partner wants to convey with emotional expressions as mentioned. Among the forms of human emotional expression, the expression of emotions through voice is perhaps the most studied. This article presents our research on speech emotion recognition using deep neural networks such as CNN, CRNN, and GRU. We used the Interactive Emotional Dyadic Motion Capture (IEMOCAP) corpus for the study with four emotions: anger, happiness, sadness, and neutrality. The feature parameters used for recognition include the Mel spectral coefficients and other parameters related to the spectrum and the intensity of the speech signal. The data augmentation was used by changing the voice and adding white noise. The results show that the GRU model gave the highest average recognition accuracy of 97.47%. This result is superior to existing studies on speech emotion recognition with the IEMOCAP corpus.
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Keyword:
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; CNN; CRNN; data augmentation; emotion; GRU; IEMOCAP; recognition; speech
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URL: https://hal.archives-ouvertes.fr/hal-03632853/document https://hal.archives-ouvertes.fr/hal-03632853 https://doi.org/10.3390/s22041414 https://hal.archives-ouvertes.fr/hal-03632853/file/sensors-22-01414-v2.pdf
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The Impact of Removing Head Movements on Audio-visual Speech Enhancement
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In: ICASSP 2022 - IEEE International Conference on Acoustics, Speech and Signal Processing ; https://hal.inria.fr/hal-03551610 ; ICASSP 2022 - IEEE International Conference on Acoustics, Speech and Signal Processing, IEEE Signal Processing Society, May 2022, Singapore, Singapore. pp.1-5 (2022)
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Face recognition improvements in adults and children with face recognition difficulties
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Face masks versus sunglasses: Limited effects of time and individual differences in the ability to judge facial identity and social traits
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An Overview of Indian Spoken Language Recognition from Machine Learning Perspective
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In: ISSN: 2375-4699 ; EISSN: 2375-4702 ; ACM Transactions on Asian and Low-Resource Language Information Processing ; https://hal.inria.fr/hal-03616853 ; ACM Transactions on Asian and Low-Resource Language Information Processing, ACM, In press, ⟨10.1145/3523179⟩ (2022)
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BBC-Oxford British Sign Language Dataset
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In: https://hal.archives-ouvertes.fr/hal-03516444 ; 2022 (2022)
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Fine-tuning pre-trained models for Automatic Speech Recognition: experiments on a fieldwork corpus of Japhug (Trans-Himalayan family)
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In: https://halshs.archives-ouvertes.fr/halshs-03647315 ; 2022 (2022)
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Evaluation of Speaker Anonymization on Emotional Speech ; Analyse de l'anonymisation du locuteur sur de la parole émotionnelle
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In: JEP2022 - Journées d'Études sur la Parole ; https://hal.archives-ouvertes.fr/hal-03636737 ; JEP2022 - Journées d'Études sur la Parole, Jun 2022, Île de Noirmoutier, France (2022)
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Can machines learn to see without visual databases?
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In: https://hal.archives-ouvertes.fr/hal-03526569 ; 2022 (2022)
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К вопросу о сущности основных конституционных обязанностей человека и гражданина ... : On the question of the essence of the basic constitutional duties of a person and a citizen ...
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Contextual time-continuous emotion recognition based on multimodal data ...
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Unsupervised quantification of entity consistency between photos and text in real-world news ...
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Müller-Budack, Eric. - : Hannover : Institutionelles Repositorium der Leibniz Universität Hannover, 2022
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Currencies of recognition: What rewards and recognition do Canadian distributed medical education preceptors value? ...
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Monolinguals and Bilinguals’ Visual Recognition Memory of Socially Relevant Stimuli at 8-10 Months. ...
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Dvoice : An open source dataset for Automatic Speech Recognition on African Languages and Dialects ...
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Dvoice : An open source dataset for Automatic Speech Recognition on African Languages and Dialects ...
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Linked Open Tafsir - Rekonstruktion der Entstehungsdynamik(en) des Korans mithilfe der Netzwerkmodellierung früher islamischer Überlieferungen ...
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