Papers by Carlos-D. Martínez-Hinarejos

3 papers
Comparison of Conventional Hybrid and CTC/Attention Decoders for Continuous Visual Speech Recognition (2024.lrec-main)

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Challenge: Recent advances have been achieved in Visual Speech Recognition (VSR) despite the lack of data, there is no clear comparison between different types of decoders for certain languages and tasks.
Approach: They focused on how the conventional DNN-HMM decoder behaves depending on the amount of data used for their estimation.
Outcome: The proposed model improves the CTC/Attention model in data-scarcity scenarios while requiring less training time and fewer parameters.
AnnoTheia: A Semi-Automatic Annotation Toolkit for Audio-Visual Speech Technologies (2024.lrec-main)

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Challenge: a small fraction of the languages currently covered by speech technologies are mainly spoken in English.
Approach: They present an annotation toolkit that detects when a person speaks on the scene and the corresponding transcription.
Outcome: The proposed toolkit can speed up the annotation process by up to four times . it can be used in Spanish, and is available on github.
LIP-RTVE: An Audiovisual Database for Continuous Spanish in the Wild (2022.lrec-1)

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Challenge: Speech perception is considered as a purely auditory process, but it is a multi-modal process involving multiple senses.
Approach: They propose to use a semi-automatically annotated audiovisual database to deal with unconstrained natural Spanish.
Outcome: The proposed system can be used to estimate speech recognition systems in the Deep Learning era.

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