Krishnateja244/Fine-tuning-of-ASR-models-on-low-resource-languages

Domain:

natural language processing

Creator:

Kri

Host:

Fine tuning ASR models such as Wave2Vec2.0, Whisper, Nemo and MMS models on low-resource languages # Fine-tuning-of-ASR-models-on-low-resource-languages Fine tuning ASR models such as Wave2Vec2.0, Whisper, Nemo and MMS models on low-resource languages ### The repository only contains report because the project is done at Fraunhofer IAIS Bonn. The project files are not open-source.

Breaking the Transcription Bottleneck: Fine-tuning ASR Models for Extremely Low-Resource Fieldwork Languages

Automatic Speech Recognition (ASR) has reached impressive accuracy for high-resource languages, yet

Fine Tuning Methods for Low-resource Languages

The rise of Large Language Models has not been inclusive of all cultures. The models are mostly trai

Fine-Tuning SLAM-ASR for Low-Resource Language Speech Recognition with High-Resource Alignment

Large language models (LLMs) have demonstrated potential in handling spoken inputs for high-resource

Fine-tuning Impact on Zero-shot XTREME-R Performance in Low-resource Languages

Intermediate-task training---fine-tuning a pretrained model on an intermediate task before fine-tuni

Impact of Sequential Fine-Tuning on Zero-Shot Euphemism Detection in Low-Resource Languages

Euphemisms are culturally variable and often ambiguous, posing challenges for language models, espec

Impact of WebFAQ Fine-Tuning on Cross-Lingual NLI Performance in Low-Resource Languages

We present WebFAQ, a large-scale collection of open-domain question answering datasets derived from

Krishnateja244/Fine-tuning-of-ASR-models-on-low-resource-languages

Domain:

Visit

Tasks