Create README.md

README.md

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+---
+license: apache-2.0
+language:
+- en
+metrics:
+- cer
+- wer
+library_name: transformers
+pipeline_tag: automatic-speech-recognition
+---
+
+# Model
+This model is [Wav2Vec2-Large-XLSR-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53)
+fine-tuned on the manually annotated subset of
+CMU's [L2-Arctic dataset](https://psi.engr.tamu.edu/l2-arctic-corpus/). It was fine-tuned
+to perform automatic phonetic transcriptions in IPA.
+It was tuned following a similar procedure as described
+by [vitouphy](https://huggingface.co/vitouphy/wav2vec2-xls-r-300m-timit-phoneme)
+with the TIMIT dataset.
+
+# Usage
+To use the model, create a pipeline and invoke it with
+the path to your WAV, which must be sampled at 16KHz.
+
+```python
+from transformers import pipeline
+
+pipe = pipeline(model="mrrubino/wav2vec2-large-xlsr-53-l2-arctic-phoneme")
+transcription = pipe("file.wav")["text"]
+```
+
+# Results
+The manually annotated subset of L2-Arctic was divided
+into training and testing datasets with a 90/10 split.
+The performance metrics for the testing dataset are
+included below.
+
+WER - 0.425
+CER - 0.128