Papers by Stephanie Hirmer

3 papers
At the Intersection of NLP and Sustainable Development: Exploring the Impact of Demographic-Aware Text Representations in Modeling Value on a Corpus of Interviews (2022.lrec-1)

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Challenge: In order to preserve the privacy of speakers, we investigate encoding demographic information using autoencoders.
Approach: They introduce a dataset of qualitative interviews from rural communities in India and Uganda and use it to enhance text representations with demographic information.
Outcome: The proposed model extends the UPV classification model with demographic information to preserve the privacy of speakers.
Natural Language Processing for Achieving Sustainable Development: the Case of Neural Labelling to Enhance Community Profiling (2020.emnlp-main)

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Challenge: In recent years, there has been an increasing interest in the application of Artificial Intelligence (AI) to the field of Sustainable Development (SD).
Approach: They propose a new extreme multi-class multi-label Automatic UserPerceived Value classification task that uses a complex corpus of interviews to investigate the problem.
Outcome: The proposed task solves a cost- and time-barrier in constructing qualitative data that prevents its widespread use and associated benefits.
Building Representative Corpora from Illiterate Communities: A Reviewof Challenges and Mitigation Strategies for Developing Countries (2021.eacl-main)

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Challenge: Existing methods for collecting data from high-income countries (HICs) make implicit assumptions about literacy and internet access, but in low-income and sub-Saharan Africa (SSA) such assumptions may not hold for LICs where the bulk of the population lives.
Approach: They propose a set of practical mitigation strategies to address the under-representation of illiterate communities in NLP corpora.
Outcome: The proposed methods address the under-representation of illiterate communities in NLP corpora and propose mitigation strategies to help future work.

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