Upload corts_valencianes_asr_a.py

corts_valencianes_asr_a.py

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+from collections import defaultdict
+import os
+import json
+import csv
+import datasets
+
+_NAME="corts_valencianes_asr_a"
+_VERSION="1.0.0"
+
+_DESCRIPTION = """
+This is the first version of CortsValencianes speech corpus for Valencian: a collection of speech recordings with transcriptions intended for Automatic Speech Recognition (ASR) applications.
+"""
+
+_CITATION = """
+@misc{bscib32024,
+      title={Corts Valencianes - Speech Corpus for Valencian ASR}, 
+      author={Baybars, Kulebi},
+      publisher={Barcelona Supercomputing Center},
+      year={2024},
+      url={},
+      }
+"""
+
+_HOMEPAGE = "https://huggingface.co/datasets/projecte-aina/corts_valencianes_asr_a"
+
+_LICENSE = "CC-BY-4.0, See https://creativecommons.org/licenses/by/4.0/deed.es"
+
+
+_BASE_DATA_DIR = "corpus/"
+
+_METADATA_CLEAN_TRAIN_SHORT =  os.path.join(_BASE_DATA_DIR,"files","clean_train_corts_short.csv")
+_METADATA_CLEAN_TEST_SHORT  =  os.path.join(_BASE_DATA_DIR,"files", "clean_test_corts_short.csv")
+_METADATA_CLEAN_DEV_SHORT   =  os.path.join(_BASE_DATA_DIR,"files",  "clean_dev_corts_short.csv")
+
+_METADATA_OTHER_TRAIN_SHORT =  os.path.join(_BASE_DATA_DIR,"files","other_train_corts_short.csv")
+_METADATA_OTHER_TEST_SHORT  =  os.path.join(_BASE_DATA_DIR,"files", "other_test_corts_short.csv")
+_METADATA_OTHER_DEV_SHORT   =  os.path.join(_BASE_DATA_DIR,"files",  "other_dev_corts_short.csv")
+
+_TARS_CLEAN_TRAIN_SHORT = os.path.join(_BASE_DATA_DIR,"files","tars_clean_train_short.paths")
+_TARS_CLEAN_TEST_SHORT  = os.path.join(_BASE_DATA_DIR,"files", "tars_clean_test_short.paths")
+_TARS_CLEAN_DEV_SHORT   = os.path.join(_BASE_DATA_DIR,"files",  "tars_clean_dev_short.paths")
+
+_TARS_OTHER_TRAIN_SHORT = os.path.join(_BASE_DATA_DIR,"files","tars_other_train_short.paths")
+_TARS_OTHER_TEST_SHORT  = os.path.join(_BASE_DATA_DIR,"files", "tars_other_test_short.paths")
+_TARS_OTHER_DEV_SHORT   = os.path.join(_BASE_DATA_DIR,"files",  "tars_other_dev_short.paths")
+
+
+_METADATA_CLEAN_TRAIN_LONG =  os.path.join(_BASE_DATA_DIR,"files","clean_train_corts_long.csv")
+_METADATA_CLEAN_TEST_LONG  =  os.path.join(_BASE_DATA_DIR,"files", "clean_test_corts_long.csv")
+_METADATA_CLEAN_DEV_LONG   =  os.path.join(_BASE_DATA_DIR,"files",  "clean_dev_corts_long.csv")
+
+_METADATA_OTHER_TRAIN_LONG =  os.path.join(_BASE_DATA_DIR,"files","other_train_corts_long.csv")
+_METADATA_OTHER_TEST_LONG =  os.path.join(_BASE_DATA_DIR,"files", "other_test_corts_long.csv")
+_METADATA_OTHER_DEV_LONG   =  os.path.join(_BASE_DATA_DIR,"files",  "other_dev_corts_long.csv")
+
+_TARS_CLEAN_TRAIN_LONG = os.path.join(_BASE_DATA_DIR,"files","tars_clean_train_long.paths")
+_TARS_CLEAN_TEST_LONG  = os.path.join(_BASE_DATA_DIR,"files", "tars_clean_test_long.paths")
+_TARS_CLEAN_DEV_LONG   = os.path.join(_BASE_DATA_DIR,"files",  "tars_clean_dev_long.paths")
+
+_TARS_OTHER_TRAIN_LONG = os.path.join(_BASE_DATA_DIR,"files","tars_other_train_long.paths")
+_TARS_OTHER_TEST_LONG  = os.path.join(_BASE_DATA_DIR,"files", "tars_other_test_long.paths")
+_TARS_OTHER_DEV_LONG   = os.path.join(_BASE_DATA_DIR,"files",  "tars_other_dev_long.paths")
+
+
+
+class CortsValencianesASRConfig(datasets.BuilderConfig):
+    """BuilderConfig for Corts Valencianes ASR"""
+
+    def __init__(self, name, **kwargs):
+        name=_NAME
+        super().__init__(name=name, **kwargs)
+
+class CortsValencianesASR(datasets.GeneratorBasedBuilder):
+    """Corts Valencianes ASR"""
+
+    VERSION = datasets.Version(_VERSION)
+    BUILDER_CONFIGS = [
+        CortsValencianesASRConfig(
+            name=_NAME,
+            version=datasets.Version(_VERSION),
+        )
+    ]
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "identifier": datasets.Value("string"),
+                "audio": datasets.Audio(sampling_rate=16000),
+                "segment_path": datasets.Value("string"),
+                "text": datasets.Value("string"),
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        
+        metadata_clean_train_short=dl_manager.download_and_extract(_METADATA_CLEAN_TRAIN_SHORT)
+        metadata_clean_test_short=dl_manager.download_and_extract(_METADATA_CLEAN_TEST_SHORT)
+        metadata_clean_dev_short=dl_manager.download_and_extract(_METADATA_CLEAN_DEV_SHORT)
+
+        metadata_other_train_short=dl_manager.download_and_extract(_METADATA_OTHER_TRAIN_SHORT)
+        metadata_other_test_short=dl_manager.download_and_extract(_METADATA_OTHER_TEST_SHORT)
+        metadata_other_dev_short=dl_manager.download_and_extract(_METADATA_OTHER_DEV_SHORT)
+
+        tars_clean_train_short=dl_manager.download_and_extract(_TARS_CLEAN_TRAIN_SHORT)
+        tars_clean_test_short=dl_manager.download_and_extract(_TARS_CLEAN_TEST_SHORT)
+        tars_clean_dev_short=dl_manager.download_and_extract(_TARS_CLEAN_DEV_SHORT)
+
+        tars_other_train_short=dl_manager.download_and_extract(_TARS_OTHER_TRAIN_SHORT)
+        tars_other_test_short=dl_manager.download_and_extract(_TARS_OTHER_TEST_SHORT)
+        tars_other_dev_short=dl_manager.download_and_extract(_TARS_OTHER_DEV_SHORT)
+        
+        
+        metadata_clean_train_long=dl_manager.download_and_extract(_METADATA_CLEAN_TRAIN_LONG)
+        metadata_clean_test_long=dl_manager.download_and_extract(_METADATA_CLEAN_TEST_LONG)
+        metadata_clean_dev_long=dl_manager.download_and_extract(_METADATA_CLEAN_DEV_LONG)
+
+        metadata_other_train_long=dl_manager.download_and_extract(_METADATA_OTHER_TRAIN_LONG)
+        metadata_other_test_long=dl_manager.download_and_extract(_METADATA_OTHER_TEST_LONG)
+        metadata_other_dev_long=dl_manager.download_and_extract(_METADATA_OTHER_DEV_LONG)
+
+        tars_clean_train_long=dl_manager.download_and_extract(_TARS_CLEAN_TRAIN_LONG)
+        tars_clean_test_long=dl_manager.download_and_extract(_TARS_CLEAN_TEST_LONG)
+        tars_clean_dev_long=dl_manager.download_and_extract(_TARS_CLEAN_DEV_LONG)
+
+        tars_other_train_long=dl_manager.download_and_extract(_TARS_OTHER_TRAIN_LONG)
+        tars_other_test_long=dl_manager.download_and_extract(_TARS_OTHER_TEST_LONG)
+        tars_other_dev_long=dl_manager.download_and_extract(_TARS_OTHER_DEV_LONG)
+       
+        hash_tar_files=defaultdict(dict)
+        with open(tars_clean_train_short,'r') as f:
+            hash_tar_files['clean_train_short']=[path.replace('\n','') for path in f]
+        with open(tars_clean_test_short,'r') as f:
+            hash_tar_files['clean_test_short']=[path.replace('\n','') for path in f]
+        with open(tars_clean_dev_short,'r') as f:
+            hash_tar_files['clean_dev_short']=[path.replace('\n','') for path in f]
+            
+        with open(tars_other_train_short,'r') as f:
+            hash_tar_files['other_train_short']=[path.replace('\n','') for path in f]
+        with open(tars_other_test_short,'r') as f:
+            hash_tar_files['other_test_short']=[path.replace('\n','') for path in f]
+        with open(tars_other_dev_short,'r') as f:
+            hash_tar_files['other_dev_short']=[path.replace('\n','') for path in f]
+            
+
+        with open(tars_clean_train_long,'r') as f:
+            hash_tar_files['clean_train_long']=[path.replace('\n','') for path in f]
+        with open(tars_clean_test_long,'r') as f:
+            hash_tar_files['clean_test_long']=[path.replace('\n','') for path in f]
+        with open(tars_clean_dev_long,'r') as f:
+            hash_tar_files['clean_dev_long']=[path.replace('\n','') for path in f]
+            
+        with open(tars_other_train_long,'r') as f:
+            hash_tar_files['other_train_long']=[path.replace('\n','') for path in f]
+        with open(tars_other_test_long,'r') as f:
+            hash_tar_files['other_test_long']=[path.replace('\n','') for path in f]
+        with open(tars_other_dev_long,'r') as f:
+            hash_tar_files['other_dev_long']=[path.replace('\n','') for path in f]
+            
+        hash_meta_paths={"clean_train_short":metadata_clean_train_short,
+        "clean_test_short":metadata_clean_test_short,
+        "clean_dev_short":metadata_clean_dev_short,
+        "other_train_short":metadata_other_train_short,
+        "other_test_short":metadata_other_test_short,
+        "other_dev_short":metadata_other_dev_short,
+        "clean_train_long":metadata_clean_train_long,
+        "clean_test_long":metadata_clean_test_long,
+        "clean_dev_long":metadata_clean_dev_long,
+        "other_train_long":metadata_other_train_long,
+        "other_test_long":metadata_other_test_long,
+        "other_dev_long":metadata_other_dev_long}
+
+        audio_paths = dl_manager.download(hash_tar_files)
+        
+        splits=["clean_train_short","clean_test_short","clean_dev_short","other_train_short","other_test_short","other_dev_short","clean_train_long","clean_test_long","clean_dev_long","other_train_long","other_test_long","other_dev_long"]
+        local_extracted_audio_paths = (
+            dl_manager.extract(audio_paths) if not dl_manager.is_streaming else
+            {
+                split:[None] * len(audio_paths[split]) for split in splits
+            }
+        )
+                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      
+        return [
+            datasets.SplitGenerator(
+                name="clean_train_short",
+                gen_kwargs={
+                    "audio_archives":[dl_manager.iter_archive(archive) for archive in audio_paths["clean_train_short"]],
+                    "local_extracted_archives_paths": local_extracted_audio_paths["clean_train_short"],
+                    "metadata_paths": hash_meta_paths["clean_train_short"],
+                }
+            ),
+            datasets.SplitGenerator(
+                name="clean_test_short",
+                gen_kwargs={
+                    "audio_archives": [dl_manager.iter_archive(archive) for archive in audio_paths["clean_test_short"]],
+                    "local_extracted_archives_paths": local_extracted_audio_paths["clean_test_short"],
+                    "metadata_paths": hash_meta_paths["clean_test_short"],
+                }
+            ),
+            datasets.SplitGenerator(
+                name="clean_dev_short",
+                gen_kwargs={
+                    "audio_archives": [dl_manager.iter_archive(archive) for archive in audio_paths["clean_dev_short"]],
+                    "local_extracted_archives_paths": local_extracted_audio_paths["clean_dev_short"],
+                    "metadata_paths": hash_meta_paths["clean_dev_short"],
+                }
+            ),
+            datasets.SplitGenerator(
+                name="other_train_short",
+                gen_kwargs={
+                    "audio_archives":[dl_manager.iter_archive(archive) for archive in audio_paths["other_train_short"]],
+                    "local_extracted_archives_paths": local_extracted_audio_paths["other_train_short"],
+                    "metadata_paths": hash_meta_paths["other_train_short"],
+                }
+            ),
+            datasets.SplitGenerator(
+                name="other_test_short",
+                gen_kwargs={
+                    "audio_archives": [dl_manager.iter_archive(archive) for archive in audio_paths["other_test_short"]],
+                    "local_extracted_archives_paths": local_extracted_audio_paths["other_test_short"],
+                    "metadata_paths": hash_meta_paths["other_test_short"],
+                }
+            ),
+            datasets.SplitGenerator(
+                name="other_dev_short",
+                gen_kwargs={
+                    "audio_archives": [dl_manager.iter_archive(archive) for archive in audio_paths["other_dev_short"]],
+                    "local_extracted_archives_paths": local_extracted_audio_paths["other_dev_short"],
+                    "metadata_paths": hash_meta_paths["other_dev_short"],
+                }
+            ),
+            datasets.SplitGenerator(
+                name="clean_train_long",
+                gen_kwargs={
+                    "audio_archives":[dl_manager.iter_archive(archive) for archive in audio_paths["clean_train_long"]],
+                    "local_extracted_archives_paths": local_extracted_audio_paths["clean_train_long"],
+                    "metadata_paths": hash_meta_paths["clean_train_long"],
+                }
+            ),
+            datasets.SplitGenerator(
+                name="clean_test_long",
+                gen_kwargs={
+                    "audio_archives": [dl_manager.iter_archive(archive) for archive in audio_paths["clean_test_long"]],
+                    "local_extracted_archives_paths": local_extracted_audio_paths["clean_test_long"],
+                    "metadata_paths": hash_meta_paths["clean_test_long"],
+                }
+            ),
+            datasets.SplitGenerator(
+                name="clean_dev_long",
+                gen_kwargs={
+                    "audio_archives": [dl_manager.iter_archive(archive) for archive in audio_paths["clean_dev_long"]],
+                    "local_extracted_archives_paths": local_extracted_audio_paths["clean_dev_long"],
+                    "metadata_paths": hash_meta_paths["clean_dev_long"],
+                }
+            ),
+            datasets.SplitGenerator(
+                name="other_train_long",
+                gen_kwargs={
+                    "audio_archives":[dl_manager.iter_archive(archive) for archive in audio_paths["other_train_long"]],
+                    "local_extracted_archives_paths": local_extracted_audio_paths["other_train_long"],
+                    "metadata_paths": hash_meta_paths["other_train_long"],
+                }
+            ),
+            datasets.SplitGenerator(
+                name="other_test_long",
+                gen_kwargs={
+                    "audio_archives": [dl_manager.iter_archive(archive) for archive in audio_paths["other_test_long"]],
+                    "local_extracted_archives_paths": local_extracted_audio_paths["other_test_long"],
+                    "metadata_paths": hash_meta_paths["other_test_long"],
+                }
+            ),
+            datasets.SplitGenerator(
+                name="other_dev_long",
+                gen_kwargs={
+                    "audio_archives": [dl_manager.iter_archive(archive) for archive in audio_paths["other_dev_long"]],
+                    "local_extracted_archives_paths": local_extracted_audio_paths["other_dev_long"],
+                    "metadata_paths": hash_meta_paths["other_dev_long"],
+                }
+            ),
+        ]
+
+    def _generate_examples(self, audio_archives, local_extracted_archives_paths, metadata_paths):
+        
+        features = ["segment_path","text"]
+        
+        with open(metadata_paths) as f:
+            metadata = {x["identifier"]: x for x in csv.DictReader(f, delimiter=",")}
+
+        for audio_archive, local_extracted_archive_path in zip(audio_archives, local_extracted_archives_paths):
+            for audio_filename, audio_file in audio_archive:
+                audio_id =os.path.splitext(os.path.basename(audio_filename))[0]
+                path = os.path.join(local_extracted_archive_path, audio_filename) if local_extracted_archive_path else audio_filename
+                                        
+                yield audio_id, {
+                    "identifier": audio_id,
+                    **{feature: metadata[audio_id][feature] for feature in features},
+                    "audio": {"path": path, "bytes": audio_file.read()},
+                }