# Low WER rate

This is a streaming Citrinet model for Ukrainian automatic speech recognition (ASR) with 141 million parameters, trained on 69 hours of Ukrainian speech data, achieving a test WER as low as 3.52%.

A Turkish speech recognition model fine-tuned on the Common Voice dataset based on Facebook's wav2vec2-large-xlsr-53 model

This is an Icelandic automatic speech recognition (ASR) model fine-tuned based on Facebook's wav2vec2-large-xlsr-53 model, trained using the Malromur dataset.

This is a Greek fine-tuned speech recognition model based on facebook/wav2vec2-large-xlsr-53, trained using the Common Voice and CSS10 datasets.

This is an automatic speech recognition model based on the wav2vec2 architecture, specifically optimized for the Tamil language and supporting Nepali speech recognition tasks.