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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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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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Abstract:
International audience ; Automatic spoken language identification (LID) is a very important research field in the era of multilingual voice-command-based human-computer interaction (HCI). A front-end LID module helps to improve the performance of many speech-based applications in the multilingual scenario. India is a populous country with diverse cultures and languages. The majority of the Indian population needs to use their respective native languages for verbal interaction with machines. Therefore, the development of efficient Indian spoken language recognition systems is useful for adapting smart technologies in every section of Indian society. The field of Indian LID has started gaining momentum in the last two decades, mainly due to the development of several standard multilingual speech corpora for the Indian languages. Even though significant research progress has already been made in this field, to the best of our knowledge, there are not many attempts to analytically review them collectively. In this work, we have conducted one of the very first attempts to present a comprehensive review of the Indian spoken language recognition research field. In-depth analysis has been presented to emphasize the unique challenges of low-resource and mutual influences for developing LID systems in the Indian contexts. Several essential aspects of the Indian LID research, such as the detailed description of the available speech corpora, the major research contributions, including the earlier attempts based on statistical modeling to the recent approaches based on different neural network architectures, and the future research trends are discussed. This review work will help assess the state of the present Indian LID research by any active researcher or any research enthusiasts from related fields.
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Keyword:
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]; [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC]; [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing; [SCCO.LING]Cognitive science/Linguistics; [SHS.LANGUE]Humanities and Social Sciences/Linguistics; [STAT.ML]Statistics [stat]/Machine Learning [stat.ML]; acoustic phonetics; code-switching; corpora development; discriminative model; Indian language identification; Language resources; language similarity; Machine learning; Signal processing systems Low-resourced languages
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URL: https://hal.inria.fr/hal-03616853/file/TALLIP_Overview.pdf
https://doi.org/10.1145/3523179
https://hal.inria.fr/hal-03616853
https://hal.inria.fr/hal-03616853/document
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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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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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Large-scale Bilingual Language-Image Contrastive Learning ...
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Bridging Video-text Retrieval with Multiple Choice Questions ...
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Towards a Perceptual Model for Estimating the Quality of Visual Speech ...
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An error correction scheme for improved air-tissue boundary in real-time MRI video for speech production ...
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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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Modeling Intensification for Sign Language Generation: A Computational Approach ...
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Keypoint based Sign Language Translation without Glosses ...
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A Transformer-Based Contrastive Learning Approach for Few-Shot Sign Language Recognition ...
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A Simple Multi-Modality Transfer Learning Baseline for Sign Language Translation ...
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Including Facial Expressions in Contextual Embeddings for Sign Language Generation ...
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Signing at Scale: Learning to Co-Articulate Signs for Large-Scale Photo-Realistic Sign Language Production ...
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Statistical and Spatio-temporal Hand Gesture Features for Sign Language Recognition using the Leap Motion Sensor ...
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Multi-View Spatial-Temporal Network for Continuous Sign Language Recognition ...
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