Advances in Language Recognition in Low Resource African Languages: The JHU-MIT Submission for NIST LRE22

Type de record:

model

Créateur:

JesJonMalSau

Éditeur:

ISCA

Hôte:

IITKGP-ABSP Submission to LRE22: Language Recognition in Low-Resource Settings

This is the detailed system description of the IITKGP-ABSP lab's submission to the NIST language rec

Advances in Low-Resource and Endangered Languages

This paper reports on the approaches and results for the collection, analysis, and processing of low

sashakhaf/speech-recognition-for-3-low-resource-african-languages

# speech-recongition-for-3-low-resource-african-languages This project aims to build an automatic s

The 2022 NIST Language Recognition Evaluation

In 2022, the U.S. National Institute of Standards and Technology (NIST) conducted the latest Languag

Robust speech recognition for low-resource languages

Process of human-machine interaction is an integral part of everyday human life in a modern world. T

Large Language Models Adaptation for Low-resource Languages: The Case for African Languages

Despite remarkable advances in Large Language Models (LLMs), African languagesremain critically underserved by the current training and adaptation pipeline. This thesisaddresses the fundamental bottlenecks in adapting LLMs for low-resource languagesthrough a uni