wav2vec2-large-xlsr-korean
| Property | Value |
|---|---|
| Parameter Count | 317M |
| License | Apache 2.0 |
| Tensor Type | F32 |
| Test WER | 4.74% |
| Test CER | 1.78% |
What is wav2vec2-large-xlsr-korean?
wav2vec2-large-xlsr-korean is a specialized speech recognition model designed specifically for the Korean language. Built on the powerful wav2vec2-XLSR architecture, this model represents a significant advancement in Korean automatic speech recognition (ASR) technology. With 317M parameters, it demonstrates impressive performance on the Zeroth Korean dataset.
Implementation Details
The model is implemented using the Transformers library and PyTorch framework. It utilizes the wav2vec2 architecture's self-supervised learning approach, optimized for Korean speech recognition. The model processes audio input at a 16kHz sampling rate and outputs text transcriptions.
- Built on wav2vec2-XLSR architecture
- Trained on the Zeroth Korean dataset
- Supports batch processing for efficient inference
- Implements CTC (Connectionist Temporal Classification) for sequence transcription
Core Capabilities
- State-of-the-art Korean speech recognition with 4.74% WER
- Character Error Rate (CER) of 1.78%
- Handles varying-length audio inputs
- Supports GPU acceleration for faster processing
- Integration with HuggingFace's Transformers library
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its exceptional performance on Korean speech recognition, achieving a low Word Error Rate of 4.74% and Character Error Rate of 1.78%. It's specifically optimized for Korean language processing and leverages the powerful wav2vec2-XLSR architecture.
Q: What are the recommended use cases?
The model is ideal for Korean speech transcription tasks, including: automated subtitling, voice command systems, voice assistants, and speech-to-text applications. It's particularly suitable for applications requiring high accuracy in Korean language processing.
