Suvach -- Generated Hindi QA benchmark
Current evaluation benchmarks for question answering (QA) in Indic languages often rely on machine translation of existing English datasets. This approach suffers from bias and inaccuracies inherent in machine translation, leading to datasets that may not reflect the true capabilities of EQA models for Indic languages. This paper proposes a new benchmark specifically designed for evaluating Hindi EQA models and discusses the methodology to do the same for any task. This method leverages large language models (LLMs) to generate a high-quality dataset in an extractive setting, ensuring its relevance for the target language. We believe this new resource will foster advancements in Hindi NLP research by providing a more accurate and reliable evaluation tool.
Code (0)
등록된 구현이 없습니다.
Tasks
Machine TranslationQuestion AnsweringTranslationSimilar Papers 제목 키워드 기반
Counter Turing Test ($CT^2$): Investigating AI-Generated Text Detection for Hindi -- Ranking LLMs based on Hindi AI Detectability Index ($ADI_{hi}$)
The widespread adoption of Large Language Models (LLMs) and awareness around multilingual LLMs have raised concerns regarding the potential risks and repercussions linked to the misapplication of AI-generated text, neces…
Text DetectionBenchmarking and Building Zero-Shot Hindi Retrieval Model with Hindi-BEIR and NLLB-E5
Given the large number of Hindi speakers worldwide, there is a pressing need for robust and efficient information retrieval systems for Hindi. Despite ongoing research, comprehensive benchmarks for evaluating retrieval m…
BenchmarkingInformation RetrievalRetrievalText RetrievalHindi-BEIR : A Large Scale Retrieval Benchmark in Hindi
Given the large number of Hindi speakers worldwide, there is a pressing need for robust and efficient information retrieval systems for Hindi. Despite ongoing research, there is a lack of comprehensive benchmark for eval…
Information RetrievalRetrievalVartani Spellcheck -- Automatic Context-Sensitive Spelling Correction of OCR-generated Hindi Text Using BERT and Levenshtein Distance
Traditional Optical Character Recognition (OCR) systems that generate text of highly inflectional Indic languages like Hindi tend to suffer from poor accuracy due to a wide alphabet set, compound characters and difficult…
named-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)NER+3Synthesizing Audio for Hindi WordNet
In this paper, we describe our work on the creation of a voice model using a speech synthesis system for the Hindi Language. We use pre-existing “voices”, use publicly available speech corpora to create a “voice” using t…
Speech Synthesis