Add task category, LeVo paper, project page, code, and sample usage, and remove redundant license

README.md

@@ -1,23 +1,72 @@
 ---
-license: apache-2.0
 language:
 - en
 - zh
+license: apache-2.0
 tags:
 - music
+task_categories:
+- automatic-speech-recognition
 ---
 
 # Song Structure and Lyric Dataset (SSLD-200)
 
-DataSet used to evaluate song structure parsing and lyrics transcription. SSLD-200 consists of 200 songs, 100 English and 100 Chinese, collected entirely from YouTube, with a total duration of 13.9 hours. 
+This dataset is used as an evaluation benchmark in the paper [LeVo: High-Quality Song Generation with Multi-Preference Alignment](https://huggingface.co/papers/2506.07520).
+
+Project page: [https://levo-demo.github.io](https://levo-demo.github.io)
+Code: [https://github.com/tencent-ailab/songgeneration](https://github.com/tencent-ailab/songgeneration)
 
-The **lyric_norm** in the format \[structure\]\[start:end\]lyric
+DataSet used to evaluate song structure parsing and lyrics transcription. SSLD-200 consists of 200 songs, 100 English and 100 Chinese, collected entirely from YouTube, with a total duration of 13.9 hours.
+
+The **lyric_norm** in the format \\[structure\\]\\[start:end\\]lyric
  - The structure is the label from StructureAnalysis for the segment.
  - The start and end are the segment’s start and end times.
  - The lyric is the recognized lyrics.
 
+## Sample Usage
+
+To use this dataset in conjunction with the associated `SongGeneration` models, follow these steps for inference.
+
+First, download the required runtime components and a specific model checkpoint:
+
+```bash
+# Download runtime components
+huggingface-cli download lglg666/SongGeneration-Runtime --local-dir ./runtime
+mv runtime/ckpt ckpt
+mv runtime/third_party third_party
+
+# Download a specific model checkpoint (e.g., SongGeneration-base-new)
+huggingface-cli download lglg666/SongGeneration-base-new --local-dir ./songgeneration_base_new
+```
+
+Once setup, you can run the inference script. You need to provide a `ckpt_path` (the directory where you downloaded the model checkpoint), an input `lyrics.jsonl` file, and an `output_path`.
+
+```bash
+sh generate.sh ckpt_path lyrics.jsonl output_path
+```
+
+**Input Format (`lyrics.jsonl`):**
+
+Each line in the `.jsonl` file represents an individual song generation request and must contain the following fields:
+
+-   `idx`: A unique identifier for the output song.
+-   `gt_lyric`: The lyrics and song structure, following the format `[Structure] Text`. For example:
+    `[intro-short] ; [verse] These faded memories of us. I can't erase the tears you cried before. Unchained this heart to find its way. My peace won't beg you to stay ; [bridge] If ever your truth still remains. Turn around and see. Life rearranged its games. All these lessons in mistakes. Even years may never erase ; [inst-short] ; [chorus] Like a fool begs for supper. I find myself waiting for her. Only to find the broken pieces of my heart. That was needed for my soul to love again ; [outro-short]`
+-   `descriptions`: (Optional) Custom text prompt for generation attributes like gender, timbre, genre, emotion, instrument, and BPM (e.g., `"female, dark, pop, sad, piano and drums."`).
+-   `prompt_audio_path`: (Optional) Path to a 10-second reference audio file.
+-   `auto_prompt_audio_type`: (Optional) Used if `prompt_audio_path` is not provided, automatically selects a reference audio based on a given style (e.g., `'Pop'`, `'R&B'`, `'Dance'`, `'Jazz'`, etc.).
+
+Example command:
+
+```bash
+sh generate.sh songgeneration_base_new sample/lyrics.jsonl sample/output
+```
+
+Additional flags can be used for specific inference scenarios, such as `--low_mem` for low-memory inference, `--not_use_flash_attn` to disable Flash Attention, or `--separate` to generate separated vocal and accompaniment tracks.
 
 ## Citation
+
+The dataset itself is detailed in the following work:
 ```
 @misc{tan2025songpreppreprocessingframeworkendtoend,
       title={SongPrep: A Preprocessing Framework and End-to-end Model for Full-song Structure Parsing and Lyrics Transcription}, 
@@ -28,7 +77,4 @@ The **lyric_norm** in the format \[structure\]\[start:end\]lyric
       primaryClass={eess.AS},
       url={https://arxiv.org/abs/2509.17404}, 
 }
-```
-
-## License
-The code and weights in this repository is released in the [LICENSE](LICENSE)  file.
+```