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Srija Anand

Srija Anand has 2 papers in our library, in 2025–2026, most of them on Question answering, Speech & spoken language, Low-resource languages; often with Atnafu Lambebo Tonja, Debela Desalegn Yadeta, Idris Abdulmumin.

2 papers in our library · 2025–2026

OpenAlex · h-index 2 · 15 works · 7 citations OpenAlex, 2026-10-14

📄 2 works in our library · ⭐ Paper Stars ranking: #12227

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Indian Institute of Technology MadrasChennai · India2024–2026 · 4 paperscurrent🎓Indraprastha Institute of Information Technology DelhiDelhi · India2020 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 8The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 workExperimental and Cognitive Psychology · 1 workPsychology · 1 workSignal Processing · 1 work

🧭 Topics 5Research subjects and languages the work is about.English · 1 workLow-resource languages · 1 workQuestion answering · 1 workSpeech & spoken language · 1 workVision & language · 1 work

 Works by year

2020s

20261 paper20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Afri-MCQA: Multimodal Cultural Question Answering for African Languages (2026)
    Afri-MCQA addresses a gap in multimodal AI evaluation. Existing cultural VQA benchmarks cover few African languages and query models only through text, even though many African languages are used mainly in spoken form. The authors built a benchmark of about 7.5k image-grounded question–answer pairs in 15 sub-Saharan…
  2. Phir Hera Fairy: An English Fairytaler is a Strong Faker of Fluent Speech in Low-Resource Indian Languages (2025)
    The paper asks whether a large English-only TTS model can be a cheap starting point for speech synthesis in low-resource Indian languages, avoiding the cost of collecting huge datasets and training from scratch.

 Co-authors here

8 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

Updated

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