Update README.md

README.md

@@ -133,7 +133,7 @@ img {
 | [![Language](https://img.shields.io/badge/Language-eu-lightgrey#model-badge)](#datasets)
 | [![Language](https://img.shields.io/badge/Language-es-lightgrey#model-badge)](#datasets)
 
-This model was specifically designed for a submission in the Bilingual Basque Spanish Speech to Text Challenge from the IBERSPEECH 2024 Albayzin evalutaions chalenges section. The train was fitted for a good performance on the challenge's evaluation splits, therefore, the performance in other splits is worse.
+This model was specifically designed for a submission in the [BBS-S2TC (Bilingual Basque Spanish Speech to Text Challenge)](https://www.isca-archive.org/iberspeech_2024/herranz24_iberspeech.html) from the IBERSPEECH 2024 Albayzin evalutaions chalenges section. The train was fitted for a good performance on the challenge's evaluation splits, therefore, the performance in other splits is worse.
 
 This model transcribes speech in lowercase Spanish alphabet including spaces, and was trained on a composite dataset comprising of 1462 hours of Spanish and Basque speech. The model was fine-tuned from a pre-trained Basque [stt_eu_conformer_transducer_large](https://huggingface.co/HiTZ/stt_eu_conformer_transducer_large) model using the [Nvidia NeMo](https://github.com/NVIDIA/NeMo) toolkit.  It is an autoregressive "large" variant of Conformer, with around 119 million parameters.
 See the [model architecture](#model-architecture) section and [NeMo documentation](https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/main/asr/models.html#conformer-transducer) for complete architecture details.