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README.md

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-# Uzbek Speech Corpus (USC): A Hugging Face Dataset Card
+# Uzbek Speech Corpus (USC)
 
-**Summary:** This repository contains the recipe for reproducing the results presented in the paper "USC: An Open-Source Uzbek Speech Corpus" ([https://arxiv.org/abs/2107.14419](https://arxiv.org/abs/2107.14419)).  The Uzbek Speech Corpus (USC) is a freely available, manually checked speech corpus comprising 958 speakers and 105 hours of transcribed audio recordings. This is, to the best of the authors' knowledge, the first open-source Uzbek speech corpus dedicated to Automatic Speech Recognition (ASR). The repository provides pre-trained models and training recipes using both DNN-HMM and end-to-end (E2E) architectures, achieving promising word error rates (WER) of 18.1% and 17.4% on validation and test sets respectively.  The code builds upon ESPnet.
+**Summary:** This repository contains dataset for reproducing the results presented in the paper "USC: An Open-Source Uzbek Speech Corpus" ([https://arxiv.org/abs/2107.14419](https://arxiv.org/abs/2107.14419)).  The Uzbek Speech Corpus (USC) is a freely available, manually checked speech corpus comprising 958 speakers and 105 hours of transcribed audio recordings. This is, to the best of the authors' knowledge, the first open-source Uzbek speech corpus dedicated to Automatic Speech Recognition (ASR). The repository provides pre-trained models and training recipes using both DNN-HMM and end-to-end (E2E) architectures, achieving promising word error rates (WER) of 18.1% and 17.4% on validation and test sets respectively.  The code builds upon ESPnet.
 
 
 **Dataset Summary:**
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 | WER (Test)       | 17.4%                                           |
 
 
-**Github Repository:** [Please insert the actual GitHub repository link here]
+**Github Repository:** https://github.com/IS2AI/Uzbek_ASR
 
 
 **Authors:**
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 - Mannon Ochilov
 - Huseyin Atakan Varol
 
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 **Citation:**
 
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