Update private_README.md

private_README.md

@@ -516,21 +516,20 @@ Data collection methods vary across individual datasets. For example, the above
 
 
 ## References
-[1] [Speaker Targeting via Self-Speaker Adaptation for Multi-talker ASR](https://arxiv.org/pdf/2506.22646)
 
-[2] [Sortformer: Seamless Integration of Speaker Diarization and ASR by Bridging Timestamps and Tokens](https://arxiv.org/abs/2409.06656)
+[1] [Sortformer: Seamless Integration of Speaker Diarization and ASR by Bridging Timestamps and Tokens](https://arxiv.org/abs/2409.06656)
 
-[3] [Streaming Sortformer: Speaker Cache-Based Online Speaker Diarization with Arrival-Time Ordering](https://arxiv.org/abs/2507.18446)
+[2] [Streaming Sortformer: Speaker Cache-Based Online Speaker Diarization with Arrival-Time Ordering](https://arxiv.org/abs/2507.18446)
 
-[4] [NEST: Self-supervised Fast Conformer as All-purpose Seasoning to Speech Processing Tasks](https://arxiv.org/abs/2408.13106)
+[3] [NEST: Self-supervised Fast Conformer as All-purpose Seasoning to Speech Processing Tasks](https://arxiv.org/abs/2408.13106)
 
-[5] [Fast Conformer with Linearly Scalable Attention for Efficient Speech Recognition](https://arxiv.org/abs/2305.05084)
+[4] [Fast Conformer with Linearly Scalable Attention for Efficient Speech Recognition](https://arxiv.org/abs/2305.05084)
 
-[6] [NVIDIA NeMo Framework](https://github.com/NVIDIA/NeMo)
+[5] [NVIDIA NeMo Framework](https://github.com/NVIDIA/NeMo)
 
-[7] [NeMo speech data simulator](https://arxiv.org/abs/2310.12371)
+[6] [NeMo speech data simulator](https://arxiv.org/abs/2310.12371)
 
-[8] [Can We Really Repurpose Multi-Speaker ASR Corpus for Speaker Diarization?](https://arxiv.org/abs/2507.09226)
+[7] [Can We Really Repurpose Multi-Speaker ASR Corpus for Speaker Diarization?](https://arxiv.org/abs/2507.09226)
 
 ## Licence