2 arrows

README.md

@@ -11,7 +11,104 @@ tags:
 pretty_name: Chest voice and Falsetto Dataset
 size_categories:
 - 1K<n<10K
-viewer: false
+dataset_info:
+  - config_name: default
+    features:
+      - name: audio
+        dtype:
+          audio:
+            sampling_rate: 22050
+      - name: mel
+        dtype: image
+      - name: label
+        dtype:
+          class_label:
+            names:
+                '0': m_chest
+                '1': f_chest
+                '2': m_falsetto
+                '3': f_falsetto
+      - name: gender
+        dtype:
+          class_label:
+            names:
+                '0': female
+                '1': male
+      - name: singing_method
+        dtype:
+          class_label:
+            names:
+                '0': falsetto
+                '1': chest
+    splits:
+      - name: train
+        num_bytes: 293944
+        num_examples: 767
+      - name: validation
+        num_bytes: 98112
+        num_examples: 256
+      - name: test
+        num_bytes: 98494
+        num_examples: 257
+    download_size: 41000619
+    dataset_size: 490550
+  - config_name: eval
+    features:
+      - name: mel
+        dtype: image
+      - name: cqt
+        dtype: image
+      - name: chroma
+        dtype: image
+      - name: label
+        dtype:
+          class_label:
+            names:
+                '0': m_chest
+                '1': f_chest
+                '2': m_falsetto
+                '3': f_falsetto
+      - name: gender
+        dtype:
+          class_label:
+            names:
+                '0': female
+                '1': male
+      - name: singing_method
+        dtype:
+          class_label:
+            names:
+                '0': falsetto
+                '1': chest
+    splits:
+      - name: train
+        num_bytes: 447819
+        num_examples: 767
+      - name: validation
+        num_bytes: 149472
+        num_examples: 256
+      - name: test
+        num_bytes: 150054
+        num_examples: 257
+    download_size: 81547911
+    dataset_size: 747345
+configs:
+  - config_name: default
+    data_files:
+      - split: train
+        path: default/train/data-*.arrow
+      - split: validation
+        path: default/validation/data-*.arrow
+      - split: test
+        path: default/test/data-*.arrow
+  - config_name: eval
+    data_files:
+      - split: train
+        path: eval/train/data-*.arrow
+      - split: validation
+        path: eval/validation/data-*.arrow
+      - split: test
+        path: eval/test/data-*.arrow
 ---
 
 # Dataset Card for Chest voice and Falsetto Dataset
@@ -115,10 +212,13 @@ for item in ds["test"]:
 
 ## Maintenance
 ```bash
-git clone [email protected]:datasets/ccmusic-database/chest_falsetto
+GIT_LFS_SKIP_SMUDGE=1 git clone [email protected]:datasets/ccmusic-database/chest_falsetto
 cd chest_falsetto
 ```
 
+## Mirror
+<https://www.modelscope.cn/datasets/ccmusic-database/chest_falsetto>
+
 ## Dataset Description
 ### Dataset Summary
 For the pre-processed version, the audio clip was into 0.25 seconds and then transformed to Mel, CQT and Chroma spectrogram in .jpg format, resulting in 8,974 files. The chest/falsetto label for each file is given as one of the four classes: m chest, m falsetto, f chest, and f falsetto. The spectrogram, the chest/falsetto label and the gender label are combined into one data entry, with the first three columns representing the Mel, CQT and Chroma. The fourth and fifth columns are the chest/falsetto label and gender label, respectively. Additionally, the integrated dataset provides the function to shuffle and split the dataset into training, validation, and test sets in an 8:1:1 ratio. This dataset can be used for singing-related tasks such as singing gender classification or chest and falsetto voice classification.
@@ -158,9 +258,6 @@ Only for chest and falsetto voices
 Recordings are cut into slices that are too short;
 The CQT spectrum column has the problem of spectrum leakage, but because the original audio slice is too short, only 0.5s, it cannot effectively avoid this problem.
 
-## Mirror
-<https://www.modelscope.cn/datasets/ccmusic-database/chest_falsetto>
-
 ## Additional Information
 ### Dataset Curators
 Zijin Li

chest_falsetto.py

@@ -1,152 +0,0 @@
-import os
-import random
-import datasets
-from datasets.tasks import ImageClassification
-
-_NAMES = {
-    "all": ["m_chest", "f_chest", "m_falsetto", "f_falsetto"],
-    "gender": ["female", "male"],
-    "singing_method": ["falsetto", "chest"],
-}
-
-_HOMEPAGE = f"https://www.modelscope.cn/datasets/ccmusic-database/{os.path.basename(__file__)[:-3]}"
-
-_DOMAIN = f"{_HOMEPAGE}/resolve/master/data"
-
-_URLS = {
-    "audio": f"{_DOMAIN}/audio.zip",
-    "mel": f"{_DOMAIN}/mel.zip",
-    "eval": f"{_DOMAIN}/eval.zip",
-}
-
-
-class chest_falsetto(datasets.GeneratorBasedBuilder):
-    def _info(self):
-        return datasets.DatasetInfo(
-            features=(
-                datasets.Features(
-                    {
-                        "audio": datasets.Audio(sampling_rate=22050),
-                        "mel": datasets.Image(),
-                        "label": datasets.features.ClassLabel(names=_NAMES["all"]),
-                        "gender": datasets.features.ClassLabel(names=_NAMES["gender"]),
-                        "singing_method": datasets.features.ClassLabel(
-                            names=_NAMES["singing_method"]
-                        ),
-                    }
-                )
-                if self.config.name == "default"
-                else datasets.Features(
-                    {
-                        "mel": datasets.Image(),
-                        "cqt": datasets.Image(),
-                        "chroma": datasets.Image(),
-                        "label": datasets.features.ClassLabel(names=_NAMES["all"]),
-                        "gender": datasets.features.ClassLabel(names=_NAMES["gender"]),
-                        "singing_method": datasets.features.ClassLabel(
-                            names=_NAMES["singing_method"]
-                        ),
-                    }
-                )
-            ),
-            supervised_keys=("mel", "label"),
-            homepage=_HOMEPAGE,
-            license="CC-BY-NC-ND",
-            version="1.2.0",
-            task_templates=[
-                ImageClassification(
-                    task="image-classification",
-                    image_column="mel",
-                    label_column="label",
-                )
-            ],
-        )
-
-    def _split_generators(self, dl_manager):
-        dataset = []
-        if self.config.name == "default":
-            files = {}
-            audio_files = dl_manager.download_and_extract(_URLS["audio"])
-            mel_files = dl_manager.download_and_extract(_URLS["mel"])
-            for fpath in dl_manager.iter_files([audio_files]):
-                fname: str = os.path.basename(fpath)
-                if fname.endswith(".wav"):
-                    item_id = fname.split(".")[0]
-                    files[item_id] = {"audio": fpath}
-
-            for fpath in dl_manager.iter_files([mel_files]):
-                fname = os.path.basename(fpath)
-                if fname.endswith(".jpg"):
-                    item_id = fname.split(".")[0]
-                    files[item_id]["mel"] = fpath
-
-            dataset = list(files.values())
-
-        else:
-            data_files = dl_manager.download_and_extract(_URLS["eval"])
-            for fpath in dl_manager.iter_files([data_files]):
-                if "mel" in fpath and os.path.basename(fpath).endswith(".jpg"):
-                    dataset.append(fpath)
-
-        categories = {}
-        for name in _NAMES["all"]:
-            categories[name] = []
-
-        for data in dataset:
-            fpath = data["audio"] if self.config.name == "default" else data
-            filename: str = os.path.basename(fpath)[:-4]
-            label = "_".join(filename.split("_")[1:3])
-            categories[label].append(data)
-
-        testset, validset, trainset = [], [], []
-        for cls in categories:
-            random.shuffle(categories[cls])
-            count = len(categories[cls])
-            p60 = int(count * 0.6)
-            p80 = int(count * 0.8)
-            trainset += categories[cls][:p60]
-            validset += categories[cls][p60:p80]
-            testset += categories[cls][p80:]
-
-        random.shuffle(trainset)
-        random.shuffle(validset)
-        random.shuffle(testset)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN, gen_kwargs={"files": trainset}
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION, gen_kwargs={"files": validset}
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST, gen_kwargs={"files": testset}
-            ),
-        ]
-
-    def _generate_examples(self, files):
-        if self.config.name == "default":
-            for i, fpath in enumerate(files):
-                file_name = os.path.basename(fpath["audio"])
-                sex = file_name.split("_")[1]
-                method = file_name.split("_")[2].split(".")[0]
-                yield i, {
-                    "audio": fpath["audio"],
-                    "mel": fpath["mel"],
-                    "label": f"{sex}_{method}",
-                    "gender": "male" if sex == "m" else "female",
-                    "singing_method": method,
-                }
-
-        else:
-            for i, fpath in enumerate(files):
-                file_name: str = os.path.basename(fpath)
-                sex = file_name.split("_")[1]
-                method = file_name.split("_")[2]
-                yield i, {
-                    "mel": fpath,
-                    "cqt": fpath.replace("mel", "cqt"),
-                    "chroma": fpath.replace("mel", "chroma"),
-                    "label": f"{sex}_{method}",
-                    "gender": "male" if sex == "m" else "female",
-                    "singing_method": method,
-                }

default/dataset_dict.json

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+{"splits": ["train", "validation", "test"]}

default/test/data-00000-of-00001.arrow

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+size 8900808

default/test/dataset_info.json

@@ -0,0 +1,91 @@
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+  "builder_name": "chest_falsetto",
+  "citation": "",
+  "config_name": "default",
+  "dataset_name": "chest_falsetto",
+  "dataset_size": 490550,
+  "description": "",
+  "download_checksums": {
+    "https://www.modelscope.cn/datasets/ccmusic-database/chest_falsetto/resolve/master/data/audio.zip": {
+      "num_bytes": 39256131,
+      "checksum": null
+    },
+    "https://www.modelscope.cn/datasets/ccmusic-database/chest_falsetto/resolve/master/data/mel.zip": {
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+      "_type": "Audio"
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+    "mel": {
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+    },
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+      "names": [
+        "m_chest",
+        "f_chest",
+        "m_falsetto",
+        "f_falsetto"
+      ],
+      "_type": "ClassLabel"
+    },
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+      "names": [
+        "female",
+        "male"
+      ],
+      "_type": "ClassLabel"
+    },
+    "singing_method": {
+      "names": [
+        "falsetto",
+        "chest"
+      ],
+      "_type": "ClassLabel"
+    }
+  },
+  "homepage": "https://www.modelscope.cn/datasets/ccmusic-database/chest_falsetto",
+  "license": "CC-BY-NC-ND",
+  "size_in_bytes": 41491169,
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+      "dataset_name": "chest_falsetto"
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+      "num_examples": 256,
+      "dataset_name": "chest_falsetto"
+    },
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+      "name": "test",
+      "num_bytes": 98494,
+      "num_examples": 257,
+      "dataset_name": "chest_falsetto"
+    }
+  },
+  "supervised_keys": {
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+}

default/test/state.json

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+  "_fingerprint": "e341c366fbee68fd",
+  "_format_columns": null,
+  "_format_kwargs": {},
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+  "_output_all_columns": false,
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+}

default/train/data-00000-of-00001.arrow

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default/train/dataset_info.json

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+}

default/train/state.json

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default/validation/data-00000-of-00001.arrow

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default/validation/dataset_info.json

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+  "description": "",
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default/validation/state.json

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eval/dataset_dict.json

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eval/test/data-00000-of-00001.arrow

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eval/test/dataset_info.json

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+  "builder_name": "chest_falsetto",
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+  "config_name": "eval",
+  "dataset_name": "chest_falsetto",
+  "dataset_size": 747345,
+  "description": "",
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+        "male"
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+      "_type": "ClassLabel"
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+      "names": [
+        "falsetto",
+        "chest"
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+      "_type": "ClassLabel"
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+  "homepage": "https://www.modelscope.cn/datasets/ccmusic-database/chest_falsetto",
+  "license": "CC-BY-NC-ND",
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+      "dataset_name": "chest_falsetto"
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+      "label_column": "label"
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+}

eval/test/state.json

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+}

eval/train/data-00000-of-00001.arrow

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