Create README.md

README.md

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+---
+license: apache-2.0
+language:
+- en
+base_model:
+- facebook/wav2vec2-large-xlsr-53
+---
+# Wav2Vec2 Fine-Tuned for Pronunciation Correction
+
+This is a fine-tuned Wav2Vec2 model for phoneme-level pronunciation correction. It analyzes speech and provides transcriptions in phonetic notation.
+
+CER = 0.1
+
+## Usage
+
+```python
+from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
+import librosa
+import torch
+
+# Load model and processor
+model = Wav2Vec2ForCTC.from_pretrained("moxeeeem/wav2vec2-finetuned-pronunciation-correction")
+processor = Wav2Vec2Processor.from_pretrained("moxeeeem/wav2vec2-finetuned-pronunciation-correction")
+
+def transcribe_audio(speech, sampling_rate):
+    inputs = processor(speech, sampling_rate=sampling_rate, return_tensors="pt")
+    with torch.no_grad():
+        logits = model(inputs.input_values).logits
+    pred_ids = torch.argmax(logits, dim=-1)
+    return processor.batch_decode(pred_ids)[0]
+
+speech, sample_rate = librosa.load("example_audio.wav", sr=16000)
+transcription = transcribe_audio(speech, sample_rate)
+print("Transcription:", transcription) # example: pɪŋɡwɪnz lɪv nɪ ði aɪsi ænɑɹtɪk