Update README.md

README.md

@@ -25,9 +25,16 @@ size_categories:
 
 # MAVL: Multilingual Audio-Video Lyrics Dataset for Animated Song Translation
 
-## Dataset Description
+<div align="center">
+  <img src="assets/mavl_logo.png" alt="MAVL Dataset Overview" width="200">
+</div>
+
+[![Hugging Face Dataset](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-MAVL-blue)](https://huggingface.co/datasets/Noename/MAVL)
+[![GitHub Repository](https://img.shields.io/badge/GitHub-MAVL--Repo-181717?logo=github)](https://github.com/k1064190/MAVL)
+[![arXiv](https://img.shields.io/badge/arXiv-2505.18614-b31b1b.svg)](https://arxiv.org/abs/2505.18614)
 
-This dataset contains a collection of YouTube URLs corresponding to songs from animated musicals. It includes meticulously aligned lyrics (English, Spanish, French, Korean, and Japanese) with corresponding timestamps, song titles, and artist information. MAVL is designed as the first multilingual, multimodal benchmark for singable lyrics translation.
+## Dataset Description
+This dataset contains a collection of YouTube URLs corresponding to songs from animated musicals. It includes meticulously aligned lyrics (English, Spanish, French, Korean, and Japanese) with corresponding timestamps, song titles, and artist information. MAVL is designed as the first multilingual, multimodal benchmark for singable lyrics translation. **To complete the dataset by downloading lyrics, audio, and video, and for related processing scripts, please refer to our [GitHub Repository](https://github.com/k1064190/MAVL).**
 
 **Crucially, this dataset does not contain the actual audio, video, or full lyric text files directly due to copyright considerations.** Instead, it provides structured metadata and URLs, along with a compact representation of lyrics (e.g., first letters of words, first/last words of lines) and their syllable counts, and precise timestamps. This allows for the reconstruction of original lyrics and the download of associated multimedia content via provided scripts.
 
@@ -36,7 +43,7 @@ This dataset contains a collection of YouTube URLs corresponding to songs from a
 The dataset is provided in a JSON format. Each entry represents a song and contains:
 
   * **Song Title:** The name of the animated song.
-  * **`lyrics`**: A nested structure containing lyric lines for each language (`US_og` for original English, `ES` for Spanish, `FR` for French, `KO` for Korean, `JA` for Japanese). Each line includes:
+  * **`lyrics`**: A nested structure containing lyric lines for each language (`US_og` for original English, `ES` for Spanish, `FR` for French, `KR` for Korean, `JP` for Japanese). Each line includes:
       * `text`: A compact representation of the original lyric line (e.g., `["Tsimp", "There's", "pants"]` for "Squirrels in my pants"). This is designed to allow for the reconstruction of the full lyric text using external resources.
       * `line_number`: The sequential number of the lyric line.
       * `syllable_count`: The syllable count of the lyric line.
@@ -90,6 +97,18 @@ The dataset is provided in a JSON format. Each entry represents a song and conta
 ]
 ```
 
+## Data Collection Methodology
+<div align="center">
+  <img src="assets/dataset_collect.png" alt="MAVL Dataset Overview" width="800">
+</div>
+The MAVL dataset was collected through a multi-step web crawling and human alignment process:
+
+1.  **Multilingual Lyrics Collection:** Metadata (song titles, artists) for English animated film music was gathered from last.fm. Original English lyrics were retrieved from Genius. Non-English lyrics corresponding to official dubbed versions were collected from platforms like lyricstranslate.com, ensuring they represent singable interpretations.
+2.  **Lyrics Human Alignment:** A crucial step involved cross-referencing original English audio/video with non-English candidate lyrics and their official dubbed audio/video to rigorously verify authenticity and exclude non-official or non-singable versions.
+3.  **Audio-Video-Lyrics Alignment:** The `stable-ts` tool (based on Whisper model) was used to generate precise timestamps, aligning audio, video, and lyrics to extract synchronized multimodal information.
+
+For more detailed information on the data collection pipeline, please refer to Section 3.1 and Appendix D of our accompanying paper.
+
 ## Intended Uses & Limitations
 
 This dataset is intended solely for **non-commercial research purposes**, such as lyrics translation, music-lyrics alignment, music information retrieval, and multimodal language model development.
@@ -102,16 +121,6 @@ This dataset is intended solely for **non-commercial research purposes**, such a
   * The dataset primarily focuses on animated musicals and may not generalize to all musical genres or styles.
   * The current lyric representation requires external processing to reconstruct full lyric text.
 
-## Data Collection Methodology
-
-The MAVL dataset was collected through a multi-step web crawling and human alignment process:
-
-1.  **Multilingual Lyrics Collection:** Metadata (song titles, artists) for English animated film music was gathered from last.fm. Original English lyrics were retrieved from Genius. Non-English lyrics corresponding to official dubbed versions were collected from platforms like lyricstranslate.com, ensuring they represent singable interpretations.
-2.  **Lyrics Human Alignment:** A crucial step involved cross-referencing original English audio/video with non-English candidate lyrics and their official dubbed audio/video to rigorously verify authenticity and exclude non-official or non-singable versions.
-3.  **Audio-Video-Lyrics Alignment:** The `stable-ts` tool (based on Whisper model) was used to generate precise timestamps, aligning audio, video, and lyrics to extract synchronized multimodal information.
-
-For more detailed information on the data collection pipeline, please refer to Section 3.1 and Appendix D of our accompanying paper.
-
 ## License
 
 This dataset is distributed under the **CC BY-NC 4.0 (Creative Commons Attribution-NonCommercial 4.0 International)** license (see the `LICENSE` file for full details). Key points include: