ArticleScientific data2023
A comprehensive multimodal dataset for contactless lip reading and acoustic analysis.
Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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11 authors.
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Abstract
Small-scale motion detection using non-invasive remote sensing techniques has recently garnered significant interest in the field of speech recognition. Our dataset paper aims to facilitate the enhancement and restoration of speech information from diverse data sources for speakers. In this paper, we introduce a novel multimodal dataset based on Radio Frequency, visual, text, audio, laser and lip landmark information, also called RVTALL. Specifically, the dataset consists of 7.5 GHz Channel Impulse Response (CIR) data from ultra-wideband (UWB) radars, 77 GHz frequency modulated continuous wave (FMCW) data from millimeter wave (mmWave) radar, visual and audio information, lip landmarks and laser data, offering a unique multimodal approach to speech recognition research. Meanwhile, a depth camera is adopted to record the landmarks of the subject's lip and voice. Approximately 400 minutes of annotated speech profiles are provided, which are collected from 20 participants speaking 5 vowels, 15 words, and 16 sentences. The dataset has been validated and has potential for the investigation of lip reading and multimodal speech recognition.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.