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1
The Impact of Removing Head Movements on Audio-visual Speech Enhancement
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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2
An Overview of Indian Spoken Language Recognition from Machine Learning Perspective
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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3
BBC-Oxford British Sign Language Dataset
In: https://hal.archives-ouvertes.fr/hal-03516444 ; 2022 (2022)
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4
Can machines learn to see without visual databases?
In: https://hal.archives-ouvertes.fr/hal-03526569 ; 2022 (2022)
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5
Large-scale Bilingual Language-Image Contrastive Learning ...
Ko, Byungsoo; Gu, Geonmo. - : arXiv, 2022
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6
Bridging Video-text Retrieval with Multiple Choice Questions ...
Ge, Yuying; Ge, Yixiao; Liu, Xihui. - : arXiv, 2022
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7
DanFEVER: claim verification dataset for Danish ...
Nørregaard, Jeppe; Derczynski, Leon. - : figshare, 2022
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8
DanFEVER: claim verification dataset for Danish ...
Nørregaard, Jeppe; Derczynski, Leon. - : figshare, 2022
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9
Towards a Perceptual Model for Estimating the Quality of Visual Speech ...
Abstract: Generating realistic lip motions to simulate speech production is key for driving natural character animations from audio. Previous research has shown that traditional metrics used to optimize and assess models for generating lip motions from speech are not a good indicator of subjective opinion of animation quality. Yet, running repetitive subjective studies for assessing the quality of animations can be time-consuming and difficult to replicate. In this work, we seek to understand the relationship between perturbed lip motion and subjective opinion of lip motion quality. Specifically, we adjust the degree of articulation for lip motion sequences and run a user-study to examine how this adjustment impacts the perceived quality of lip motion. We then train a model using the scores collected from our user-study to automatically predict the subjective quality of an animated sequence. Our results show that (1) users score lip motions with slight over-articulation the highest in terms of perceptual quality; (2) ... : Submitted to Interspeech 2022 ...
Keyword: Audio and Speech Processing eess.AS; Computer Vision and Pattern Recognition cs.CV; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering; Graphics cs.GR; Sound cs.SD
URL: https://dx.doi.org/10.48550/arxiv.2203.10117
https://arxiv.org/abs/2203.10117
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10
An error correction scheme for improved air-tissue boundary in real-time MRI video for speech production ...
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11
Expression-preserving face frontalization improves visually assisted speech processing ...
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12
WLASL-LEX: a Dataset for Recognising Phonological Properties in American Sign Language ...
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13
Modeling Intensification for Sign Language Generation: A Computational Approach ...
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14
Keypoint based Sign Language Translation without Glosses ...
Kim, Youngmin; Kwak, Minji; Lee, Dain. - : arXiv, 2022
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15
A Transformer-Based Contrastive Learning Approach for Few-Shot Sign Language Recognition ...
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16
A Simple Multi-Modality Transfer Learning Baseline for Sign Language Translation ...
Chen, Yutong; Wei, Fangyun; Sun, Xiao. - : arXiv, 2022
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17
Including Facial Expressions in Contextual Embeddings for Sign Language Generation ...
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18
Signing at Scale: Learning to Co-Articulate Signs for Large-Scale Photo-Realistic Sign Language Production ...
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19
Statistical and Spatio-temporal Hand Gesture Features for Sign Language Recognition using the Leap Motion Sensor ...
Bird, Jordan J.. - : arXiv, 2022
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20
Multi-View Spatial-Temporal Network for Continuous Sign Language Recognition ...
Li, Ronghui; Meng, Lu. - : arXiv, 2022
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