Generating Contextually-Relevant Navigation Instructions for Blind and Low Vision People
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866911952697032704 |
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| author | Merchant, Zain Anwar, Abrar Wang, Emily Chattopadhyay, Souti Thomason, Jesse |
| author_facet | Merchant, Zain Anwar, Abrar Wang, Emily Chattopadhyay, Souti Thomason, Jesse |
| contents | Navigating unfamiliar environments presents significant challenges for blind and low-vision (BLV) individuals. In this work, we construct a dataset of images and goals across different scenarios such as searching through kitchens or navigating outdoors. We then investigate how grounded instruction generation methods can provide contextually-relevant navigational guidance to users in these instances. Through a sighted user study, we demonstrate that large pretrained language models can produce correct and useful instructions perceived as beneficial for BLV users. We also conduct a survey and interview with 4 BLV users and observe useful insights on preferences for different instructions based on the scenario. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_08219 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Generating Contextually-Relevant Navigation Instructions for Blind and Low Vision People Merchant, Zain Anwar, Abrar Wang, Emily Chattopadhyay, Souti Thomason, Jesse Computation and Language Human-Computer Interaction Navigating unfamiliar environments presents significant challenges for blind and low-vision (BLV) individuals. In this work, we construct a dataset of images and goals across different scenarios such as searching through kitchens or navigating outdoors. We then investigate how grounded instruction generation methods can provide contextually-relevant navigational guidance to users in these instances. Through a sighted user study, we demonstrate that large pretrained language models can produce correct and useful instructions perceived as beneficial for BLV users. We also conduct a survey and interview with 4 BLV users and observe useful insights on preferences for different instructions based on the scenario. |
| title | Generating Contextually-Relevant Navigation Instructions for Blind and Low Vision People |
| topic | Computation and Language Human-Computer Interaction |
| url | https://arxiv.org/abs/2407.08219 |