Updated model information

README.md

@@ -1,3 +1,40 @@
 ---
 license: apache-2.0
+datasets:
+- mozilla-foundation/common_voice_10_0
+base_model:
+- facebook/wav2vec2-xls-r-300m
+tags:
+- pytorch
+- phoneme-recognition
+pipeline_tag: automatic-speech-recognition
 ---
+
+Model Information
+=================
+
+Allophant is a multilingual phoneme recognizer trained on spoken sentences in 34 languages, capable of generalizing zero-shot to unseen phoneme inventories.
+
+The model is based on [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) and was pre-trained on a subset of the [Common Voice Corpus 10.0](https://huggingface.co/datasets/mozilla-foundation/common_voice_10_0) transcribed with [eSpeak NG](https://github.com/espeak-ng/espeak-ng).
+
+| Model Name       | UCLA Phonetic Corpus (PER) | UCLA Phonetic Corpus (AER) | Common Voice (PER) | Common Voice (AER) |
+| ---------------- | ---------: | ---------: | -------: | -------: |
+| [Multitask](https://huggingface.co/kgnlp/allophant)        | **45.62%** | 19.44% | **34.34%** | **8.36%** |
+| **Hierarchical**     | 46.09% | **19.18%** | 34.35% | 8.56% |
+| [Multitask Shared](https://huggingface.co/kgnlp/allophant-shared) | 46.05% | 19.52% | 41.20% | 8.88% |
+| [Baseline Shared](https://huggingface.co/kgnlp/allophant-baseline-shared)  | 48.25% |   -    | 45.35% |  -    |
+| [Baseline](https://huggingface.co/kgnlp/allophant-baseline)         | 57.01% |   -    | 46.95% |  -    |
+
+Note that our baseline models were trained without phonetic feature classifiers and therefore only support phoneme recognition.
+
+Citation
+========
+
+```bibtex
+@inproceedings{glocker2023allophant,
+    title={Allophant: Cross-lingual Phoneme Recognition with Articulatory Attributes},
+    author={Glocker, Kevin and Herygers, Aaricia and Georges, Munir},
+    year={2023},
+    booktitle={{Proc. Interspeech 2023}},
+    month={8}}
+```