Papers by Tanja Schultz
Uncovering the Full Potential of Visual Grounding Methods in VQA (2024.acl-long)
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| Challenge: | Visual Grounding (VG) methods in VQA aim to strengthen a model's reliance on question-relevant visual information. |
| Approach: | They propose to strengthen a model's reliance on question-relevant visual information by using a visual grounding method that is based on a question-related visual input. |
| Outcome: | The proposed methods can be much more effective when evaluation conditions are corrected. |
Analysis of GlobalPhone and Ethiopian Languages Speech Corpora for Multilingual ASR (2020.lrec-1)
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| Challenge: | Using global phone data, we can develop multilingual speech recognition systems in yet unsupported languages. |
| Approach: | They analyze phonetic overlaps between GlobalPhone and Ethiopian speech corpora to develop multilingual Automatic Speech Recognition system for the Ethiopian languages. |
| Outcome: | The proposed system will be able to support three different languages and have morphological complexity. |
Measuring Faithful and Plausible Visual Grounding in VQA (2023.findings-emnlp)
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| Challenge: | Lack of visual grounding (VG) in VQA systems can manifest in over-reliance on irrelevant image parts or a disregard for the visual modality entirely. |
| Approach: | They propose a new metric that measures if a model identifies question-relevant objects in the scene and relies on the information contained in the relevant objects when producing its answer. |
| Outcome: | The proposed metric measures if a model identifies question-relevant objects in the scene and relies on the information contained in the relevant objects when producing its answer. |
Automatic Speech Recognition for Uyghur through Multilingual Acoustic Modeling (2020.lrec-1)
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| Challenge: | Low-resource languages suffer from lower performance of Automatic Speech Recognition (ASR) due to the lack of data. |
| Approach: | They propose to use Turkish as donor language to train acoustic models using multilingual training to achieve more context coverage. |
| Outcome: | The proposed system performs better with multilingual training for the under-resourced Uyghur language. |