w2v-xls-r-uk
| Property | Value |
|---|---|
| Parameter Count | 315M |
| License | Apache 2.0 |
| Base Model | facebook/wav2vec2-xls-r-300m |
| Best WER | 4.63% (with LM) |
What is w2v-xls-r-uk?
w2v-xls-r-uk is a state-of-the-art Ukrainian speech recognition model based on the wav2vec2-xls-r-300m architecture. Created by Yehor, this model has been specifically optimized for Ukrainian language processing, featuring support for apostrophes and hyphens.
Implementation Details
The model is built upon the XLS-R framework and has been trained on the Mozilla Common Voice 10.0 dataset. It implements advanced language modeling capabilities, achieving impressive Word Error Rate (WER) metrics across different versions of the Common Voice dataset.
- Trained on Mozilla Common Voice 10.0 Ukrainian dataset
- Implements F32 tensor type for computations
- Includes specialized handling for Ukrainian-specific characters
- Incorporates language model optimization
Core Capabilities
- Achieves 4.63% WER on CV10 with language model
- 11.8% Character Error Rate (CER) with language model
- Handles Ukrainian text with proper apostrophe and hyphen support
- Compatible with Transformers framework
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its specialized optimization for Ukrainian language processing, particularly in handling language-specific characters and achieving very low error rates with language model integration.
Q: What are the recommended use cases?
The model is ideal for Ukrainian speech recognition tasks, particularly in applications requiring high accuracy and proper handling of Ukrainian-specific text features. It's suitable for both academic and production environments.
