Update README.md

README.md

@@ -53,7 +53,6 @@ img {
 [![Paper](https://img.shields.io/badge/Paper-ICASSP%202025-green)](https://arxiv.org/abs/2502.14673)
 [![Model size](https://img.shields.io/badge/Params-110M-lightgrey#model-badge)](#description)
 
-**!!!ATTENTION: Input audio must be MONO (1 channel) at 16,000 sample rate** 
 ---
 ## Table of contents
 1. [Model Description](#description)
@@ -134,11 +133,16 @@ Example Output:
 If you use this work in your research, please cite:
 
 ```bibtex
-@inproceedings{chunkformer,
-  title={ChunkFormer: Masked Chunking Conformer For Long-Form Speech Transcription},
-  author={Khanh Le, Tuan Vu Ho, Dung Tran and Duc Thanh Chau},
-  booktitle={ICASSP},
-  year={2025}
+@INPROCEEDINGS{10888640,
+  author={Le, Khanh and Ho, Tuan Vu and Tran, Dung and Chau, Duc Thanh},
+  booktitle={ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, 
+  title={ChunkFormer: Masked Chunking Conformer For Long-Form Speech Transcription}, 
+  year={2025},
+  volume={},
+  number={},
+  pages={1-5},
+  keywords={Scalability;Memory management;Graphics processing units;Signal processing;Performance gain;Hardware;Resource management;Speech processing;Standards;Context modeling;chunkformer;masked batch;long-form transcription},
+  doi={10.1109/ICASSP49660.2025.10888640}}
 }
 ```