  This paper presents the MasonTigers entry to the SemEval-2024 Task 1 -
Semantic Textual Relatedness. The task encompasses supervised (Track A),
unsupervised (Track B), and cross-lingual (Track C) approaches across 14
different languages. MasonTigers stands out as one of the two teams who
participated in all languages across the three tracks. Our approaches achieved
rankings ranging from 11th to 21st in Track A, from 1st to 8th in Track B, and
from 5th to 12th in Track C. Adhering to the task-specific constraints, our
best performing approaches utilize ensemble of statistical machine learning
approaches combined with language-specific BERT based models and sentence
transformers.
