Improve Balalaika dataset card: Correct license, add paper and code links, and add 'russian' tag

This PR addresses several improvements for the Balalaika dataset card:

1. **Corrected License:** The metadata's `license` tag has been updated from `cc-by-nc-sa-4.0` to `cc-by-nc-nd-4.0` to accurately reflect the license stated for the dataset within the "License" section of the card.
2. **Added Paper and Code Links:** Explicit links to the associated paper ([https://huggingface.co/papers/2507.13563](https://huggingface.co/papers/2507.13563)) and the GitHub repository ([https://github.com/mtuciru/balalaika](https://github.com/mtuciru/balalaika)) have been added prominently at the top of the dataset card's content for easier access.
3. **Added 'russian' Tag:** A `russian` tag has been added to the metadata to improve the dataset's discoverability for users searching for Russian language resources.

These changes enhance the clarity, accuracy, and navigability of the dataset card.

README.md

@@ -1,14 +1,18 @@
 ---
-license: cc-by-nc-sa-4.0
 language:
 - ru
+license: cc-by-nc-nd-4.0
 task_categories:
 - text-to-speech
 pretty_name: Balalaika
+tags:
+- russian
 ---
 
 # A Data-Centric Framework for Addressing Phonetic and Prosodic Challenges in Russian Speech Generative Models
 
+[Paper](https://huggingface.co/papers/2507.13563) | [Code](https://github.com/mtuciru/balalaika)
+
 Russian speech synthesis presents distinctive challenges, including vowel reduction, consonant devoicing, variable stress patterns, homograph ambiguity, and unnatural intonation. This paper introduces Balalaika, a novel dataset comprising more than 2,000 hours of studio-quality Russian speech with comprehensive textual annotations, including punctuation and stress markings. Experimental results show that models trained on Balalaika significantly outperform those trained on existing datasets in both speech synthesis and enhancement tasks.
 
 ---