Convert dataset to Parquet

README.md

@@ -71,16 +71,16 @@ dataset_info:
     dtype: int8
   splits:
   - name: train
-    num_bytes: 1626283624
+    num_bytes: 1624802079.0
     num_examples: 51093
   - name: validation
-    num_bytes: 217204539
+    num_bytes: 217003968.304
     num_examples: 6799
   - name: test
-    num_bytes: 98979965
+    num_bytes: 98888548.326
     num_examples: 3081
-  download_size: 1454702755
-  dataset_size: 1942468128
+  download_size: 1794668711
+  dataset_size: 1940694595.6299999
 - config_name: v0.02
   features:
   - name: file
@@ -137,19 +137,36 @@ dataset_info:
     dtype: int8
   splits:
   - name: train
-    num_bytes: 2684381672
+    num_bytes: 2681496094.824
     num_examples: 84848
   - name: validation
-    num_bytes: 316435178
+    num_bytes: 316135541.396
     num_examples: 9982
   - name: test
-    num_bytes: 157096106
+    num_bytes: 156951097.18
     num_examples: 4890
-  download_size: 2285975869
-  dataset_size: 3157912956
+  download_size: 2908293664
+  dataset_size: 3154582733.3999996
 config_names:
 - v0.01
 - v0.02
+configs:
+- config_name: v0.01
+  data_files:
+  - split: train
+    path: v0.01/train-*
+  - split: validation
+    path: v0.01/validation-*
+  - split: test
+    path: v0.01/test-*
+- config_name: v0.02
+  data_files:
+  - split: train
+    path: v0.02/train-*
+  - split: validation
+    path: v0.02/validation-*
+  - split: test
+    path: v0.02/test-*
 ---
 
 # Dataset Card for SpeechCommands
@@ -221,7 +238,6 @@ Example of a core word (`"label"` is a word, `"is_unknown"` is `False`):
 {
   "file": "no/7846fd85_nohash_0.wav", 
   "audio": {
-    "path": "no/7846fd85_nohash_0.wav", 
     "array": array([ -0.00021362, -0.00027466, -0.00036621, ...,  0.00079346,
           0.00091553,  0.00079346]), 
     "sampling_rate": 16000
@@ -238,7 +254,6 @@ Example of an auxiliary word (`"label"` is a word, `"is_unknown"` is `True`)
 {
   "file": "tree/8b775397_nohash_0.wav", 
   "audio": {
-    "path": "tree/8b775397_nohash_0.wav", 
     "array": array([ -0.00854492, -0.01339722, -0.02026367, ...,  0.00274658,
           0.00335693,  0.0005188]), 
     "sampling_rate": 16000
@@ -256,7 +271,6 @@ Example of background noise (`_silence_`) class:
 {
   "file": "_silence_/doing_the_dishes.wav", 
   "audio": {
-    "path": "_silence_/doing_the_dishes.wav", 
     "array": array([ 0.        ,  0.        ,  0.        , ..., -0.00592041,
          -0.00405884, -0.00253296]), 
     "sampling_rate": 16000

speech_commands.py

@@ -1,229 +0,0 @@
-# coding=utf-8
-# Copyright 2021 The HuggingFace Datasets Authors and the current dataset script contributor.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-"""Speech Commands, an audio dataset of spoken words designed to help train and evaluate keyword spotting systems. """
-
-
-import textwrap
-
-import datasets
-
-
-_CITATION = """
-@article{speechcommandsv2,
-   author = { {Warden}, P.},
-    title = "{Speech Commands: A Dataset for Limited-Vocabulary Speech Recognition}",
-  journal = {ArXiv e-prints},
-  archivePrefix = "arXiv",
-  eprint = {1804.03209},
-  primaryClass = "cs.CL",
-  keywords = {Computer Science - Computation and Language, Computer Science - Human-Computer Interaction},
-    year = 2018,
-    month = apr,
-    url = {https://arxiv.org/abs/1804.03209},
-}
-"""
-
-_DESCRIPTION = """
-This is a set of one-second .wav audio files, each containing a single spoken
-English word or background noise. These words are from a small set of commands, and are spoken by a
-variety of different speakers. This data set is designed to help train simple
-machine learning models. This dataset is covered in more detail at
-[https://arxiv.org/abs/1804.03209](https://arxiv.org/abs/1804.03209).
-
-Version 0.01 of the data set (configuration `"v0.01"`) was released on August 3rd 2017 and contains
-64,727 audio files.
-
-In version 0.01 thirty different words were recoded: "Yes", "No", "Up", "Down", "Left",
-"Right", "On", "Off", "Stop", "Go", "Zero", "One", "Two", "Three", "Four", "Five", "Six", "Seven", "Eight", "Nine",
-"Bed", "Bird", "Cat", "Dog", "Happy", "House", "Marvin", "Sheila", "Tree", "Wow".
-
-
-In version 0.02 more words were added: "Backward", "Forward", "Follow", "Learn", "Visual".
-
-In both versions, ten of them are used as commands by convention: "Yes", "No", "Up", "Down", "Left",
-"Right", "On", "Off", "Stop", "Go". Other words are considered to be auxiliary (in current implementation
-it is marked by `True` value of `"is_unknown"` feature). Their function is to teach a model to distinguish core words
-from unrecognized ones.
-
-The `_silence_` class contains a set of longer audio clips that are either recordings or
-a mathematical simulation of noise.
-
-"""
-
-_LICENSE = "Creative Commons BY 4.0 License"
-
-_URL = "https://www.tensorflow.org/datasets/catalog/speech_commands"
-
-_DL_URL = "https://s3.amazonaws.com/datasets.huggingface.co/SpeechCommands/{name}/{name}_{split}.tar.gz"
-
-WORDS = [
-    "yes",
-    "no",
-    "up",
-    "down",
-    "left",
-    "right",
-    "on",
-    "off",
-    "stop",
-    "go",
-]
-
-UNKNOWN_WORDS_V1 = [
-    "zero",
-    "one",
-    "two",
-    "three",
-    "four",
-    "five",
-    "six",
-    "seven",
-    "eight",
-    "nine",
-    "bed",
-    "bird",
-    "cat",
-    "dog",
-    "happy",
-    "house",
-    "marvin",
-    "sheila",
-    "tree",
-    "wow",
-]
-
-UNKNOWN_WORDS_V2 = UNKNOWN_WORDS_V1 + [
-    "backward",
-    "forward",
-    "follow",
-    "learn",
-    "visual",
-]
-
-SILENCE = "_silence_"  # background noise
-LABELS_V1 = WORDS + UNKNOWN_WORDS_V1 + [SILENCE]
-LABELS_V2 = WORDS + UNKNOWN_WORDS_V2 + [SILENCE]
-
-
-class SpeechCommandsConfig(datasets.BuilderConfig):
-    """BuilderConfig for SpeechCommands."""
-
-    def __init__(self, labels, **kwargs):
-        super(SpeechCommandsConfig, self).__init__(**kwargs)
-        self.labels = labels
-
-
-class SpeechCommands(datasets.GeneratorBasedBuilder):
-    BUILDER_CONFIGS = [
-        SpeechCommandsConfig(
-            name="v0.01",
-            description=textwrap.dedent(
-                """\
-                Version 0.01 of the SpeechCommands dataset. Contains 30 words
-                (20 of them are auxiliary) and background noise.
-                """
-            ),
-            labels=LABELS_V1,
-            version=datasets.Version("0.1.0"),
-        ),
-        SpeechCommandsConfig(
-            name="v0.02",
-            description=textwrap.dedent(
-                """\
-                Version 0.02 of the SpeechCommands dataset.
-                Contains 35 words (25 of them are auxiliary) and background noise.
-                """
-            ),
-            labels=LABELS_V2,
-            version=datasets.Version("0.2.0"),
-        ),
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "file": datasets.Value("string"),
-                    "audio": datasets.features.Audio(sampling_rate=16_000),
-                    "label": datasets.ClassLabel(names=self.config.labels),
-                    "is_unknown": datasets.Value("bool"),
-                    "speaker_id": datasets.Value("string"),
-                    "utterance_id": datasets.Value("int8"),
-                }
-            ),
-            homepage=_URL,
-            citation=_CITATION,
-            license=_LICENSE,
-            version=self.config.version,
-        )
-
-    def _split_generators(self, dl_manager):
-
-        archive_paths = dl_manager.download(
-            {
-                "train": _DL_URL.format(name=self.config.name, split="train"),
-                "validation": _DL_URL.format(name=self.config.name, split="validation"),
-                "test": _DL_URL.format(name=self.config.name, split="test"),
-            }
-        )
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "archive": dl_manager.iter_archive(archive_paths["train"]),
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
-                gen_kwargs={
-                    "archive": dl_manager.iter_archive(archive_paths["validation"]),
-                },
-            ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "archive": dl_manager.iter_archive(archive_paths["test"]),
-                },
-            ),
-        ]
-
-    def _generate_examples(self, archive):
-        for path, file in archive:
-            if not path.endswith(".wav"):
-                continue
-
-            word, audio_filename = path.split("/")
-            is_unknown = False
-
-            if word == SILENCE:
-                speaker_id, utterance_id = None, 0
-
-            else:  # word is either in WORDS or unknown
-                if word not in WORDS:
-                    is_unknown = True
-                # an audio filename looks like `0bac8a71_nohash_0.wav`
-                speaker_id, _, utterance_id = audio_filename.split(".wav")[0].split("_")
-
-            yield path, {
-                "file": path,
-                "audio": {"path": path, "bytes": file.read()},
-                "label": word,
-                "is_unknown": is_unknown,
-                "speaker_id": speaker_id,
-                "utterance_id": utterance_id,
-            }

v0.01/test-00000-of-00001.parquet

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