Update dataset card: Correct license, add paper/code links, and expand tags

This PR improves the Balalaika dataset card by:
- Correcting the `license` metadata tag to `cc-by-nc-nd-4.0`, which is the specific license for the dataset as stated in the "License" section of the README.
- Adding direct links to the paper ([A Data-Centric Framework for Addressing Phonetic and Prosodic Challenges in Russian Speech Generative Models](https://huggingface.co/papers/2507.13563)) and the GitHub repository (`https://github.com/mtuciru/balalaika`) at the top of the dataset card for better discoverability.
- Expanding the `tags` metadata with `russian`, `speech-synthesis`, `speech-enhancement`, and `audio` to reflect the dataset's characteristics and use cases.

README.md

@@ -1,14 +1,22 @@
 ---
-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
+- speech-synthesis
+- speech-enhancement
+- audio
 ---
 
 # A Data-Centric Framework for Addressing Phonetic and Prosodic Challenges in Russian Speech Generative Models
 
+Paper: [https://huggingface.co/papers/2507.13563](https://huggingface.co/papers/2507.13563)
+Code: [https://github.com/mtuciru/balalaika](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.
 
 ---