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Found 9 papers, 3 papers with code
Clause Final Verb Prediction in Hindi: Evidence for Noisy Channel Model of Communication
The models differ in their use of prior context during the prediction process – the context is either noisy or noise-free.
Towards Universal Segmentations: UniSegments 1.0
Our work aims at developing a multilingual data resource for morphological segmentation.
Constrained Decoding for Technical Term Retention in English-Hindi MT
Technical terms may require special handling when the target audience is bilingual, depending on the cultural and educational norms of the society in question.
Towards Handling Verb Phrase Ellipsis in English-Hindi Machine Translation
English-Hindi machine translation systems have difficulty interpreting verb phrase ellipsis (VPE) in English, and commit errors in translating sentences with VPE.
LID Models are Actually Accent Classifiers: Implications and Solutions for LID on Accented Speech
Prior research indicates that LID model performance significantly declines on accented speech; however, the specific causes, extent, and characterization of these errors remain under-explored.
DialUp! Modeling the Language Continuum by Adapting Models to Dialects and Dialects to Models
Most of the world's languages and dialects are low-resource, and lack support in mainstream machine translation (MT) models.
Evaluating Large Language Models along Dimensions of Language Variation: A Systematik Invesdigatiom uv Cross-lingual Generalization
While large language models exhibit certain cross-lingual generalization capabilities, they suffer from performance degradation (PD) on unseen closely-related languages (CRLs) and dialects relative to their high-resource language neighbour (HRLN).
Pointer-Generator Networks for Low-Resource Machine Translation: Don't Copy That!
While Transformer-based neural machine translation (NMT) is very effective in high-resource settings, many languages lack the necessary large parallel corpora to benefit from it.
When your Cousin has the Right Connections: Unsupervised Bilingual Lexicon Induction for Related Data-Imbalanced Languages
Most existing approaches for unsupervised bilingual lexicon induction (BLI) depend on good quality static or contextual embeddings requiring large monolingual corpora for both languages.
