Upload mumospee_small.py with huggingface_hub

mumospee_small.py

@@ -14,8 +14,8 @@ This is the small version include no more 1000 rows.
 
 _LICENSE = "Creative Commons Attribution 4.0 International"
 
-# Defining categories or tags for filtering
-_LANGUAGES = ["en", "bg", "de", "es", "it", "ar"]  # Example languages
+_LANGUAGES = ["en", "bg", "de", "ar"] 
+
 _TAGS = ["CoVoST", "GigaSpeech", "peoples_speech", "Librispeech", "LibriTTS", "Emilia", "MOSEL"]
 
 _SPLITS = ["train", "validation", "test"]
@@ -25,12 +25,27 @@ class MumospeeDatasetConfig(datasets.BuilderConfig):
     def __init__(self, split, language=None, tag=None, **kwargs):
         super().__init__(**kwargs)
         self.split=split
-        self.language = language
-        self.tag = tag
+
+        # Convert string inputs to single-item lists, or use as-is if already a list
+        self.language = [language] if isinstance(language, str) else language or []
+        self.tag = [tag] if isinstance(tag, str) else tag or []
+
+        # Validate each provided language
+        for lang in self.language:
+            if lang not in self._LANGUAGES:
+                raise ValueError(
+                    f"Invalid language: '{lang}'. Accepted languages are: {', '.join(self.ACCEPTED_LANGUAGES)}."
+                )
+
+        # Validate each provided tag
+        for t in self.tag:
+            if t not in self._TAGS:
+                raise ValueError(
+                    f"Invalid dataset origin: '{t}'. Accepted tags are: {', '.join(self.ACCEPTED_TAGS)}."
+                )
 
 
 class MumospeeDataset(datasets.GeneratorBasedBuilder):
-    """Your custom dataset for Hugging Face based on the CSV metadata and audio URLs."""
 
     VERSION = datasets.Version("1.0.0")
 
@@ -75,6 +90,24 @@ class MumospeeDataset(datasets.GeneratorBasedBuilder):
 
         csv_path = dl_manager.download_and_extract("dataset.csv")
 
+
+        # ===To download the url
+        # Load CSV to retrieve URLs for audio files
+        # data = pd.read_csv(csv_path)
+        # url_list = data["url"].tolist()  # List of all URLs in the CSV file
+        # url_list = list(set(url_list))
+
+        # # Download all files listed in the 'url' column and store the local paths
+        # downloaded_files = dl_manager.download(url_list)
+
+        # # Add the downloaded file paths to the DataFrame to make them accessible in `_generate_examples`
+        # data["local_path"] = downloaded_files
+
+        #===
+
+
+
+
         # Define the splits and pass the language and tag filters to _generate_examples
         return [
             datasets.SplitGenerator(
@@ -93,37 +126,36 @@ class MumospeeDataset(datasets.GeneratorBasedBuilder):
 
 
     def _generate_examples(self, filepath):
-        """Generate examples from the CSV data and audio URLs."""
-        # Use dl_manager to get the CSV file from the Hugging Face repo
-        # csv_file = dl_manager.download_and_extract("metadata.csv")
-        # Read the CSV metadata
-       
+
         data = pd.read_csv(filepath)
-        # Filter by primary split
         split=self.config.split
       
 
         language=self.config.language
         tag=self.config.tag
 
-        print(f"filepath is {filepath}, split is {split}, lang is {self.config.language}, tag is {self.config.tag}")
-
+        print(f'Return {split} dataset in langauge of {self.config.language}, originally from {self.config.tag}.')
 
         data_split = data[data["split"] == split]
+
+
         if language:
-            data_split = data_split[data_split["language"] == language]
+            data_split = data_split[data_split["language"].isin(language)]
         if tag:
-            data_split = data_split[data_split["tag"] == tag]
-        
-        for i, row in data_split.iterrows():
+            data_split = data_split[data_split["tag"].isin(tag)]
 
-            # Construct the full audio path or URL
-            audio_url = row["url"]
+        
+        if data_split.empty:
+            print(f"No data found for split='{split}', language='{language}', tag='{tag}'. Returning None.")
+            return  # This exits the generator without yielding any examples
 
-            # Prepare the data entry for this example
+        
+        for i, row in data_split.iterrows():
             yield i, {
                 "path": row["path"],
-                "audio": audio_url,
+                #"local_path": row["local_path"],
+                "url": row["url"],
+                "type": row["type"],
                 "duration": float(row["duration"]),
                 "language": row["language"],
                 "transcript": row["transcript"],
@@ -134,34 +166,6 @@ class MumospeeDataset(datasets.GeneratorBasedBuilder):
 
 
 
-        # with open(csv_file, mode='r', encoding='utf-8') as f:
-        #     reader = csv.DictReader(f)
-        #     for row in reader:
-        #         # Filter by tag or language here if necessary
-        #         if row["language"] not in _LANGUAGES:
-        #             continue  # Skip entries with unsupported languages
-        #         if row["tag"] not in _TAGS:
-        #             continue  # Skip entries with unsupported tags
-
-
-
-
-        #         # Construct the full audio path or URL
-        #         audio_url = row["url"]
-
-        #         # Prepare the data entry for this example
-        #         yield row["path"], {
-        #             "audio": audio_url,
-        #             "duration": float(row["duration"]),
-        #             "language": row["language"],
-        #             "transcript": row["transcript"],
-        #             "tag": row["tag"],
-        #             "split": row["split"],
-        #             "license": row["license"]
-        #         }
-
-
-
     def _download_audio(self, audio_url):
         """Download audio from a URL if needed (you could also implement streaming)."""
         # This is an example function for downloading audio if it's needed