24 citations · 83 across the 67 of their papers we have counts for
16 papers · 1 filter
PortraitTalk: Towards Customizable One-Shot Audio-to-Talking Face Generation
Fatemeh Nazarieh, Zhenhua Feng, Diptesh Kanojia +2
Audio-driven talking face generation is a challenging task in digital communication. Despite significant progress in the area, most existing methods concentrate on audio-lip synchr…
BESSTIE: A Benchmark for Sentiment and Sarcasm Classification for Varieties of English
Dipankar Srirag, Aditya Joshi, Jordan Painter +1
Despite large language models (LLMs) being known to exhibit bias against non-standard language varieties, there are no known labelled datasets for sentiment analysis of English. To…
Experiences from Creating a Benchmark for Sentiment Classification for Varieties of English
Dipankar Srirag, Jordan Painter, Aditya Joshi +1
Existing benchmarks often fail to account for linguistic diversity, like language variants of English. In this paper, we share our experiences from our ongoing project of building…
A Survey of Multimodal Sarcasm Detection
Shafkat Farabi, Tharindu Ranasinghe, Diptesh Kanojia +2
Sarcasm is a rhetorical device that is used to convey the opposite of the literal meaning of an utterance. Sarcasm is widely used on social media and other forms of computer-mediat…
Together We Can: Multilingual Automatic Post-Editing for Low-Resource Languages
Sourabh Deoghare, Diptesh Kanojia, Pushpak Bhattacharyya
This exploratory study investigates the potential of multilingual Automatic Post-Editing (APE) systems to enhance the quality of machine translations for low-resource Indo-Aryan la…
Centrality-aware Product Retrieval and Ranking
Hadeel Saadany, Swapnil Bhosale, Samarth Agrawal +3
This paper addresses the challenge of improving user experience on e-commerce platforms by enhancing product ranking relevant to users' search queries. Ambiguity and complexity of…
What do Large Language Models Need for Machine Translation Evaluation?
Shenbin Qian, Archchana Sindhujan, Minnie Kabra +4
Leveraging large language models (LLMs) for various natural language processing tasks has led to superlative claims about their performance. For the evaluation of machine translati…
Are Large Language Models State-of-the-art Quality Estimators for Machine Translation of User-generated Content?
Shenbin Qian, Constantin Orăsan, Diptesh Kanojia +1
This paper investigates whether large language models (LLMs) are state-of-the-art quality estimators for machine translation of user-generated content (UGC) that contains emotional…
Edit Distances and Their Applications to Downstream Tasks in Research and Commercial Contexts
Félix do Carmo, Diptesh Kanojia
The tutorial describes the concept of edit distances applied to research and commercial contexts. We use Translation Edit Rate (TER), Levenshtein, Damerau-Levenshtein, Longest Comm…
A Multi-task Learning Framework for Evaluating Machine Translation of Emotion-loaded User-generated Content
Shenbin Qian, Constantin Orăsan, Diptesh Kanojia +1
Machine translation (MT) of user-generated content (UGC) poses unique challenges, including handling slang, emotion, and literary devices like irony and sarcasm. Evaluating the qua…
Connecting Ideas in 'Lower-Resource' Scenarios: NLP for National Varieties, Creoles and Other Low-resource Scenarios
Aditya Joshi, Diptesh Kanojia, Heather Lent +2
Despite excellent results on benchmarks over a small subset of languages, large language models struggle to process text from languages situated in `lower-resource' scenarios such…
AV-GS: Learning Material and Geometry Aware Priors for Novel View Acoustic Synthesis
Swapnil Bhosale, Haosen Yang, Diptesh Kanojia +2
Novel view acoustic synthesis (NVAS) aims to render binaural audio at any target viewpoint, given a mono audio emitted by a sound source at a 3D scene. Existing methods have propos…
Unsupervised Audio-Visual Segmentation with Modality Alignment
Swapnil Bhosale, Haosen Yang, Diptesh Kanojia +2
Audio-Visual Segmentation (AVS) aims to identify, at the pixel level, the object in a visual scene that produces a given sound. Current AVS methods rely on costly fine-grained anno…
Airavata: Introducing Hindi Instruction-tuned LLM
Jay Gala, Thanmay Jayakumar, Jaavid Aktar Husain +8
We announce the initial release of "Airavata," an instruction-tuned LLM for Hindi. Airavata was created by fine-tuning OpenHathi with diverse, instruction-tuning Hindi datasets to…
Google Translate Error Analysis for Mental Healthcare Information: Evaluating Accuracy, Comprehensibility, and Implications for Multilingual Healthcare Communication
Jaleh Delfani, Constantin Orasan, Hadeel Saadany +5
This study explores the use of Google Translate (GT) for translating mental healthcare (MHealth) information and evaluates its accuracy, comprehensibility, and implications for mul…
Natural Language Processing for Dialects of a Language: A Survey
Aditya Joshi, Raj Dabre, Diptesh Kanojia +4
State-of-the-art natural language processing (NLP) models are trained on massive training corpora, and report a superlative performance on evaluation datasets. This survey delves i…