Update README.md

README.md

@@ -16,25 +16,29 @@ tags:
 
 In [CLaMP: Contrastive Language-Music Pre-training for Cross-Modal Symbolic Music Information Retrieval](https://ai-muzic.github.io/clamp/), we introduce WikiMusicText (WikiMT), a new dataset for the evaluation of semantic search and music classification. It includes 1010 lead sheets in ABC notation sourced from Wikifonia.org, each accompanied by a title, artist, genre, and description. The title and artist information is extracted from the score, whereas the genre labels are obtained by matching keywords from the Wikipedia entries and assigned to one of the 8 classes (Jazz, Country, Folk, R&B, Pop, Rock, Dance, and Latin) that loosely mimic the GTZAN genres. The description is obtained by utilizing BART-large to summarize and clean the corresponding Wikipedia entry. Additionally, the natural language information within the ABC notation is removed.
 
-WikiMT is a unique resource to support the evaluation of semantic search and music classification. However, it is important to acknowledge that the dataset was curated from publicly available sources, and there may be limitations concerning the accuracy and completeness of the genre and description information. Further research is needed to explore the potential biases and limitations of the dataset and to develop strategies to address them. Therefore, to support additional investigations, we also provide the [source files](https://github.com/microsoft/muzic/blob/main/clamp/wikimusictext/source_files.zip) of WikiMT, including the MusicXML files from Wikifonia and the original entries from Wikipedia.
+WikiMT is a unique resource to support the evaluation of semantic search and music classification. However, it is important to acknowledge that the dataset was curated from publicly available sources, and there may be limitations concerning the accuracy and completeness of the genre and description information. Further research is needed to explore the potential biases and limitations of the dataset and to develop strategies to address them.
 
-## Obtaining ABC Notation Music Scores
+Certainly, let's maintain a more concise and to-the-point style in GitHub readme fashion:
 
-To access ABC notation music scores from the WikiMT dataset, you will need to follow these steps:
+Apologies for the oversight. Here's the revised section that includes the "provided code":
 
-1. **Find the Wikifonia Data Link:** The code provided does not offer a direct link to download Wikifonia.zip. To obtain the Wikifonia dataset, you must first locate a download link for the ABC notation data. You can search for it on the internet or on Wikifonia-related websites.
+## How to Obtain ABC Notation Music Scores
 
-2. **Run the Provided Code:** After finding the download link for the Wikifonia ABC notation data, you can execute the provided Python code. The code will prompt you to input the URL from which to fetch the ABC notation data. 
+To access ABC notation music scores from the WikiMT dataset, follow these steps:
 
-   For example, you will be prompted to enter the URL as follows:
-   
-   ```python
-   Enter the Wikifonia URL: [Paste your URL here]
-   ```
+1. **Download WikiMT Metadata:** Get the metadata file for WikiMT [here](https://huggingface.co/datasets/sander-wood/wikimusictext/resolve/main/wikimusictext.jsonl). This file has important dataset information.
 
-   Paste the URL to the Wikifonia.zip file and press Enter. The code will then proceed to download, process, and extract the musical content, making it accessible for your research or applications.
+2. **Get the `xml2abc.py` Script:** Download the `xml2abc.py` script from [this link](https://wim.vree.org/svgParse/xml2abc.html) and save it in your local directory.
 
-By following these steps, you can successfully obtain ABC notation music scores from the WikiMT dataset after providing the necessary download link.
+3. **Find Wikifonia MusicXML Data Link:** Locate a download link for the Wikifonia dataset in MusicXML format (with .mxl extension). You can search the internet or Wikifonia-related websites for it.
+
+4. **Run the Provided Code:** After acquiring the WikiMT metadata, the `xml2abc.py` script, and the Wikifonia MusicXML data link, execute the provided Python code below. It'll prompt you for the Wikifonia data URL, like this:
+
+```python
+Enter the Wikifonia URL: [Paste your URL here]
+```
+
+Paste your URL pointing to the Wikifonia.zip file and press Enter. The code will take care of downloading, processing, and extracting the music content, making it ready for your research or applications.
 
 ```python
 import subprocess
@@ -81,7 +85,7 @@ def filter(lines):
 def load_music(filename):
     # Convert the file to ABC notation
     p = subprocess.Popen(
-        f'cmd /u /c python xml2abc_145/xml2abc.py -m 2 -c 6 -x "{filename}"',
+        f'cmd /u /c python xml2abc.py -m 2 -c 6 -x "{filename}"',
         stdout=subprocess.PIPE,
         stderr=subprocess.PIPE,
         shell=True
@@ -120,9 +124,6 @@ def download_and_extract(url):
     else:
         print("Failed to download the file. HTTP response code:", response.status_code)
 
-# Special thanks to Wim Vree for xml2abc.py
-download_and_extract("https://wim.vree.org/svgParse/xml2abc.py-145.zip")
-
 # Download the Wikifonia dataset
 wikifonia_url = input("Enter the Wikifonia URL: ")
 download_and_extract(wikifonia_url)
@@ -145,6 +146,9 @@ with open("wikimusictext.jsonl", "w", encoding="utf-8") as f:
         f.write(json.dumps(song, ensure_ascii=False)+"\n")
 ```
 
+By following these steps and running the provided code, you can efficiently access ABC notation music scores from the WikiMT dataset. Just ensure you have the metadata, the `xml2abc.py` script, and the correct download link before starting. Enjoy your musical journey!
+
+
 ## Copyright Disclaimer
 WikiMT was curated from publicly available sources, and all rights to the original content and data remain with their respective copyright holders. The dataset is made available for research and educational purposes, and any use, distribution, or modification of the dataset should comply with the terms and conditions set forth by the original data providers.