saattrupdan/wav2vec2-xls-r-300m-ftspeech
🧠 AI Modelsaattrupdan
A fine-tuned Wav2Vec2 model optimized for high-accuracy Danish automatic speech recognition.
The saattrupdan/wav2vec2-xls-r-300m-ftspeech model leverages the powerful XLS-R architecture, which is a large-scale cross-lingual speech representation model. By fine-tuning this 300 million parameter base model on the ftspeech dataset, the author has created a specialized tool for Danish ASR. The model utilizes the Connectionist Temporal Classification (CTC) loss function, making it highly efficient for transcribing audio streams into text. It is fully compatible with the PyTorch framework and supports the safetensors format for secure and fast model loading. This model is particularly effective for tasks requiring low-latency transcription of Danish speech, benefiting from the pre-trained cross-lingual features of the original XLS-R model while being adapted for specific linguistic nuances found in the ftspeech corpus.
💡Highlights
- ├─300M parameter XLS-R architecture
- ├─Optimized for Danish ASR tasks
- └─900k+ downloads on Hugging Face
🎯For
- ├─Speech Engineers
- ├─NLP Researchers
- └─Danish App Developers