Update README.md

README.md

@@ -6,4 +6,44 @@ language:
 - en
 library_name: nemo
 ---
-not ready
+# SpellMapper - Spellchecking ASR Customization Model 
+
+<style>
+img {
+ display: inline;
+}
+</style>
+
+| [![Language](https://img.shields.io/badge/Language-en--US-lightgrey#model-badge)](#datasets)
+
+This model is an alternative to word boosting/shallow fusion approaches:
+
+- does not require retraining ASR model;
+- does not require beam-search/language model (LM);
+- can be applied on top of any English ASR model output;
+
+Paper: [SpellMapper: A non-autoregressive neural spellchecker for ASR customization with candidate retrieval based on n-gram mappings](https://arxiv.org/abs/2306.02317)
+
+
+
+## How to Use this Model
+
+To use this model you will need to install [NVIDIA NeMo](https://github.com/NVIDIA/NeMo).
+
+See [Bash-script](https://github.com/NVIDIA/NeMo/blob/main/examples/nlp/spellchecking_asr_customization/run_infer.sh) with example of inference pipeline.
+
+Or play with [Tutorial](https://github.com/NVIDIA/NeMo/blob/stable/tutorials/nlp/SpellMapper_English_ASR_Customization.ipynb).
+
+
+## Citation
+
+```bibtex
+    @misc{antonova2023spellmapper,
+      title={SpellMapper: A non-autoregressive neural spellchecker for ASR customization with candidate retrieval based on n-gram mappings}, 
+      author={Alexandra Antonova and Evelina Bakhturina and Boris Ginsburg},
+      year={2023},
+      eprint={2306.02317},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+    }
+```