New Capability to Look Up an ASL Sign from a Video Example
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866911960813010944 |
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| author | Neidle, Carol Opoku, Augustine Ballard, Carey Zhou, Yang He, Xiaoxiao Dimitriadis, Gregory Metaxas, Dimitris |
| author_facet | Neidle, Carol Opoku, Augustine Ballard, Carey Zhou, Yang He, Xiaoxiao Dimitriadis, Gregory Metaxas, Dimitris |
| contents | Looking up an unknown sign in an ASL dictionary can be difficult. Most ASL dictionaries are organized based on English glosses, despite the fact that (1) there is no convention for assigning English-based glosses to ASL signs; and (2) there is no 1-1 correspondence between ASL signs and English words. Furthermore, what if the user does not know either the meaning of the target sign or its possible English translation(s)? Some ASL dictionaries enable searching through specification of articulatory properties, such as handshapes, locations, movement properties, etc. However, this is a cumbersome process and does not always result in successful lookup. Here we describe a new system, publicly shared on the Web, to enable lookup of a video of an ASL sign (e.g., a webcam recording or a clip from a continuous signing video). The user submits a video for analysis and is presented with the five most likely sign matches, in decreasing order of likelihood, so that the user can confirm the selection and then be taken to our ASLLRP Sign Bank entry for that sign. Furthermore, this video lookup is also integrated into our newest version of SignStream(R) software to facilitate linguistic annotation of ASL video data, enabling the user to directly look up a sign in the video being annotated, and, upon confirmation of the match, to directly enter into the annotation the gloss and features of that sign, greatly increasing the efficiency and consistency of linguistic annotations of ASL video data. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_13571 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | New Capability to Look Up an ASL Sign from a Video Example Neidle, Carol Opoku, Augustine Ballard, Carey Zhou, Yang He, Xiaoxiao Dimitriadis, Gregory Metaxas, Dimitris Computer Vision and Pattern Recognition Computation and Language Looking up an unknown sign in an ASL dictionary can be difficult. Most ASL dictionaries are organized based on English glosses, despite the fact that (1) there is no convention for assigning English-based glosses to ASL signs; and (2) there is no 1-1 correspondence between ASL signs and English words. Furthermore, what if the user does not know either the meaning of the target sign or its possible English translation(s)? Some ASL dictionaries enable searching through specification of articulatory properties, such as handshapes, locations, movement properties, etc. However, this is a cumbersome process and does not always result in successful lookup. Here we describe a new system, publicly shared on the Web, to enable lookup of a video of an ASL sign (e.g., a webcam recording or a clip from a continuous signing video). The user submits a video for analysis and is presented with the five most likely sign matches, in decreasing order of likelihood, so that the user can confirm the selection and then be taken to our ASLLRP Sign Bank entry for that sign. Furthermore, this video lookup is also integrated into our newest version of SignStream(R) software to facilitate linguistic annotation of ASL video data, enabling the user to directly look up a sign in the video being annotated, and, upon confirmation of the match, to directly enter into the annotation the gloss and features of that sign, greatly increasing the efficiency and consistency of linguistic annotations of ASL video data. |
| title | New Capability to Look Up an ASL Sign from a Video Example |
| topic | Computer Vision and Pattern Recognition Computation and Language |
| url | https://arxiv.org/abs/2407.13571 |