SyMCoM - Syntactic Measure of Code Mixing A Study Of English-Hindi Code-Mixing

no code implementations • Findings (ACL) 2022 • Prashant Kodali, Anmol Goel, Monojit Choudhury, Manish Shrivastava, Ponnurangam Kumaraguru

Code mixing is the linguistic phenomenon where bilingual speakers tend to switch between two or more languages in conversations.

POS

CoMeT: Towards Code-Mixed Translation Using Parallel Monolingual Sentences

1 code implementation • NAACL (CALCS) 2021 • Devansh Gautam, Prashant Kodali, Kshitij Gupta, Anmol Goel, Manish Shrivastava, Ponnurangam Kumaraguru

Code-mixed languages are very popular in multilingual societies around the world, yet the resources lag behind to enable robust systems on such languages.

Machine Translation Translation

HashSet - A Dataset For Hashtag Segmentation

1 code implementation • LREC 2022 • Prashant Kodali, Akshala Bhatnagar, Naman Ahuja, Manish Shrivastava, Ponnurangam Kumaraguru

HashSet dataset is sampled from a different set of tweets when compared to existing datasets and provides an alternate distribution of hashtags to build and validate hashtag segmentation models.

Segmentation Specificity

Benchmarks Underestimate the Readiness of Multi-lingual Dialogue Agents

no code implementations • 28 May 2024 • Andrew H. Lee, Sina J. Semnani, Galo Castillo-López, Gäel de Chalendar, Monojit Choudhury, Ashna Dua, Kapil Rajesh Kavitha, Sungkyun Kim, Prashant Kodali, Ponnurangam Kumaraguru, Alexis Lombard, Mehrad Moradshahi, Gihyun Park, Nasredine Semmar, Jiwon Seo, Tianhao Shen, Manish Shrivastava, Deyi Xiong, Monica S. Lam

However, after manual evaluation of the validation set, we find that by correcting gold label errors and improving dataset annotation schema, GPT-4 with our prompts can achieve (1) 89. 6%-96. 8% accuracy in DST, and (2) more than 99% correct response generation across different languages.

Dialogue State Tracking In-Context Learning +1

From Human Judgements to Predictive Models: Unravelling Acceptability in Code-Mixed Sentences

no code implementations • 9 May 2024 • Prashant Kodali, Anmol Goel, Likhith Asapu, Vamshi Krishna Bonagiri, Anirudh Govil, Monojit Choudhury, Manish Shrivastava, Ponnurangam Kumaraguru

To this end, we construct Cline - a dataset containing human acceptability judgements for English-Hindi (en-hi) code-mixed text.

X-RiSAWOZ: High-Quality End-to-End Multilingual Dialogue Datasets and Few-shot Agents

1 code implementation • 30 Jun 2023 • Mehrad Moradshahi, Tianhao Shen, Kalika Bali, Monojit Choudhury, Gaël de Chalendar, Anmol Goel, Sungkyun Kim, Prashant Kodali, Ponnurangam Kumaraguru, Nasredine Semmar, Sina J. Semnani, Jiwon Seo, Vivek Seshadri, Manish Shrivastava, Michael Sun, Aditya Yadavalli, Chaobin You, Deyi Xiong, Monica S. Lam

We create a new multilingual benchmark, X-RiSAWOZ, by translating the Chinese RiSAWOZ to 4 languages: English, French, Hindi, Korean; and a code-mixed English-Hindi language.

Entity Alignment Machine Translation +1

PreCogIIITH at HinglishEval : Leveraging Code-Mixing Metrics & Language Model Embeddings To Estimate Code-Mix Quality

1 code implementation • 16 Jun 2022 • Prashant Kodali, Tanmay Sachan, Akshay Goindani, Anmol Goel, Naman Ahuja, Manish Shrivastava, Ponnurangam Kumaraguru

Code-Mixing is a phenomenon of mixing two or more languages in a speech event and is prevalent in multilingual societies.

Data Augmentation Language Modeling +1

HashSet -- A Dataset For Hashtag Segmentation

2 code implementations • 18 Jan 2022 • Prashant Kodali, Akshala Bhatnagar, Naman Ahuja, Manish Shrivastava, Ponnurangam Kumaraguru

HashSet dataset is sampled from a different set of tweets when compared to existing datasets and provides an alternate distribution of hashtags to build and validate hashtag segmentation models.

Segmentation Specificity

Battling Hateful Content in Indic Languages HASOC '21

1 code implementation • Forum for Information Retrieval Evaluation (FIRE) 2021 • Aditya Kadam, Anmol Goel, Jivitesh Jain, Jushaan Singh Kalra, Mallika Subramanian, Manvith Reddy, Prashant Kodali, T. H. Arjun, Manish Shrivastava, Ponnurangam Kumaraguru

We adopt a multilingual transformer based approach and describe our architecture for all 6 subtasks as part of the challenge.

Hate Speech Detection