Update README.md

README.md

@@ -276,7 +276,7 @@ NVIDIA [NeMo Canary](https://nvidia.github.io/NeMo/blogs/2024/2024-02-canary/) i
 
 Canary is an encoder-decoder model with FastConformer [1] encoder and Transformer Decoder [2]. 
 With audio features extracted from the encoder, task tokens such as `<source language>`, `<target language>`, `<task>` and `<toggle PnC>` 
-are fed into the Transformer Decoder to trigger the text generation process. Canary uses a concatenated tokenizer from individual 
+are fed into the Transformer Decoder to trigger the text generation process. Canary uses a concatenated tokenizer [5] from individual 
 SentencePiece [3] tokenizers of each language, which makes it easy to scale up to more languages. 
 The Canay-1B model has 24 encoder layers and 24 layers of decoder layers in total.
 
@@ -479,7 +479,7 @@ BLEU score on [FLEURS](https://huggingface.co/datasets/google/fleurs) test set:
 
 | **Version** | **Model** | **En->De** | **En->Es** | **En->Fr** | **De->En** | **Es->En** | **Fr->En** |
 |:-----------:|:---------:|:----------:|:----------:|:----------:|:----------:|:----------:|:----------:|
-| 1.23.0      | canary-1b | 22.66	   | 41.11      | 40.76      | 32.64      | 32.15      | 23.57      |
+| 1.23.0      | canary-1b | 32.13	   | 22.66      | 40.76      | 33.98      | 21.80      | 30.95      |
 
 
 BLEU score on [COVOST-v2](https://github.com/facebookresearch/covost) test set:
@@ -518,6 +518,7 @@ Check out [Riva live demo](https://developer.nvidia.com/riva#demos).
 
 [4] [NVIDIA NeMo Toolkit](https://github.com/NVIDIA/NeMo)
 
+[5] [Unified Model for Code-Switching Speech Recognition and Language Identification Based on Concatenated Tokenizer](https://aclanthology.org/2023.calcs-1.7.pdf)
 
 ## Licence