Upload bvcc-voicemos2022.py

bvcc-voicemos2022.py

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+# coding=utf-8
+# Copyright 2020 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.
+# TODO: Address all TODOs and remove all explanatory comments
+"""TODO: Add a description here."""
+
+
+import csv
+import json
+import os
+
+import datasets
+
+_CITATION = """\
+@misc{cooper2021generalization,
+    title={Generalization Ability of MOS Prediction Networks}, 
+    author={Erica Cooper and Wen-Chin Huang and Tomoki Toda and Junichi Yamagishi},
+    year={2021},
+    eprint={2110.02635},
+    archivePrefix={arXiv},
+    primaryClass={eess.AS}
+}
+"""
+
+# TODO: Add description of the dataset here
+# You can copy an official description
+_DESCRIPTION = """\
+This dataset is for internal use only. For voicemos challenge
+"""
+
+# TODO: Add a link to an official homepage for the dataset here
+_HOMEPAGE = "https://codalab.lisn.upsaclay.fr/competitions/695"
+
+# TODO: Add the licence for the dataset here if you can find it
+_LICENSE = "INTERNAL"
+
+
+class BvccDataset(datasets.GeneratorBasedBuilder):
+    """BVCC dataset for voicemos challenge 2022"""
+
+    VERSION = datasets.Version("1.1.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="main_track",
+            version=VERSION,
+            description="main track dataset by wavfiles",
+        ),
+        datasets.BuilderConfig(
+            name="main_track_listeners",
+            version=VERSION,
+            description="main track dataset by listener rating",
+        ),
+        datasets.BuilderConfig(
+            name="ood_track", version=VERSION, description="Out of domain dataset"
+        ),
+        datasets.BuilderConfig(
+            name="ood_track_unlabeled",
+            version=VERSION,
+            description="Out of domain dataset unlabeled",
+        ),
+        datasets.BuilderConfig(
+            name="ood_track_listeners",
+            version=VERSION,
+            description="ood track dataset by listener rating",
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = "main_track"  # It's not mandatory to have a default configuration. Just use one if it make sense.
+
+    def _info(self):
+        # TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset
+        if (
+            self.config.name == "main_track"
+        ):  # This is the name of the configuration selected in BUILDER_CONFIGS above
+            features = datasets.Features(
+                {
+                    "path": datasets.Value("string"),
+                    "audio": datasets.Audio(sampling_rate=16_000),
+                    "sysID": datasets.Value("string"),
+                    "uttID": datasets.Value("string"),
+                    "averaged rating": datasets.Value("float32"),
+                    # These are the features of your dataset like images, labels ...
+                }
+            )
+        elif self.config.name == "main_track_listeners":
+            # sysID,uttID,rating,ignore,listenerinfo
+            # {}_AGERANGE_LISTENERID_GENDER_[ignore]_[ignore]_HEARINGIMPAIRMENT
+            features = datasets.Features(
+                {
+                    "path": datasets.Value("string"),
+                    "audio": datasets.Audio(sampling_rate=16_000),
+                    "sysID": datasets.Value("string"),
+                    "uttID": datasets.Value("string"),
+                    "rating": datasets.Value("int8"),
+                    "age range": datasets.Value("string"),
+                    "listener id": datasets.Value("string"),
+                    "gender": datasets.Value("string"),
+                    "hearing impairment": datasets.Value("string"),
+                }
+            )
+        elif (
+            self.config.name == "ood_track"
+        ):  # This is the name of the configuration selected in BUILDER_CONFIGS above
+            features = datasets.Features(
+                {
+                    "path": datasets.Value("string"),
+                    "audio": datasets.Audio(sampling_rate=16_000),
+                    "sysID": datasets.Value("string"),
+                    "uttID": datasets.Value("string"),
+                    "averaged rating": datasets.Value("float32"),
+                    # These are the features of your dataset like images, labels ...
+                }
+            )
+        elif self.config.name == "ood_track_listeners":
+            # sysID,uttID,rating,ignore,listenerinfo
+            # {}_AGERANGE_LISTENERID_GENDER_[ignore]_[ignore]_HEARINGIMPAIRMENT
+            features = datasets.Features(
+                {
+                    "path": datasets.Value("string"),
+                    "audio": datasets.Audio(sampling_rate=16_000),
+                    "sysID": datasets.Value("string"),
+                    "uttID": datasets.Value("string"),
+                    "rating": datasets.Value("int8"),
+                    "age range": datasets.Value("string"),
+                    "listener id": datasets.Value("string"),
+                    "gender": datasets.Value("string"),
+                    "hearing impairment": datasets.Value("string"),
+                }
+            )
+        elif self.config.name == "ood_track_unlabeled":
+            # sysID,uttID,rating,ignore,listenerinfo
+            # {}_AGERANGE_LISTENERID_GENDER_[ignore]_[ignore]_HEARINGIMPAIRMENT
+            features = datasets.Features(
+                {
+                    "path": datasets.Value("string"),
+                    "audio": datasets.Audio(sampling_rate=16_000),
+                    "sysID": datasets.Value("string"),
+                    "uttID": datasets.Value("string"),
+                }
+            )
+        else:
+            raise ValueError(f"invalid config name {self.config.name}")
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        # TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
+        # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
+
+        # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS
+        # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files.
+        # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive
+        data_dir = self.config.data_dir
+        if "listeners" in self.config.name:
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TRAIN,
+                    # These kwargs will be passed to _generate_examples
+                    gen_kwargs={
+                        "filepath": os.path.join(data_dir, "DATA/sets/TRAINSET"),
+                        "split": "train",
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name=datasets.Split.VALIDATION,
+                    # These kwargs will be passed to _generate_examples
+                    gen_kwargs={
+                        "filepath": os.path.join(data_dir, "DATA/sets/DEVSET"),
+                        "split": "dev",
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name=datasets.Split.TEST,
+                    # These kwargs will be passed to _generate_examples
+                    gen_kwargs={
+                        "filepath": os.path.join(data_dir, "DATA/sets/TESTSET"),
+                        "split": "test",
+                    },
+                ),
+            ]
+        elif "unlabeled" in self.config.name:
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TRAIN,
+                    # These kwargs will be passed to _generate_examples
+                    gen_kwargs={
+                        "filepath": os.path.join(
+                            data_dir, "DATA/sets/unlabeled_mos_list.txt"
+                        ),
+                        "split": "train",
+                    },
+                ),
+            ]
+        else:
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TRAIN,
+                    # These kwargs will be passed to _generate_examples
+                    gen_kwargs={
+                        "filepath": os.path.join(
+                            data_dir, "DATA/sets/train_mos_list.txt"
+                        ),
+                        "split": "train",
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name=datasets.Split.VALIDATION,
+                    # These kwargs will be passed to _generate_examples
+                    gen_kwargs={
+                        "filepath": os.path.join(
+                            data_dir, "DATA/sets/val_mos_list.txt"
+                        ),
+                        "split": "dev",
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name=datasets.Split.TEST,
+                    # These kwargs will be passed to _generate_examples
+                    gen_kwargs={
+                        "filepath": os.path.join(data_dir, "DATA/sets/TESTSET"),
+                        "split": "test",
+                    },
+                ),
+            ]
+
+    # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
+    def _generate_examples(self, filepath, split):
+        # TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
+        # The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example.
+        with open(filepath, encoding="utf-8") as f:
+            for key, row in enumerate(f.readlines()):
+                data = row.strip().split(",")
+                if self.config.name == "main_track":
+                    sysID, uttID = data[0].split("-")
+                    uttID = uttID.replace(".wav", "")
+                    if len(data) > 1:
+                        score = data[1]
+                    else:
+                        score = 999
+                    # Yields examples as (key, example) tuples
+                    path = os.path.join(self.config.data_dir, "DATA/wav/", data[0])
+                    yield key, {
+                        "path": path,
+                        "audio": path,
+                        "sysID": sysID,
+                        "uttID": uttID,
+                        "averaged rating": score,
+                    }
+                elif self.config.name == "main_track_listeners":
+                    if len(data) > 1:
+                        rating = data[1]
+                        sysID, path, rating, _, listenerinfo = data
+                        _, age, listenrID, gender, _, _, hearingImpairement = (
+                            listenerinfo.split("_")
+                        )
+                    else:
+                        sysID, uttID = data[0].split("-")
+                        uttID = uttID.replace(".wav", "")
+                        rating = 999
+                        age = 999
+                        listenrID = 999
+                        gender = 999
+                        path = data[0]
+                    uttID = path.split("-")[-1]
+                    uttID = uttID.replace(".wav", "")
+                    path = os.path.join(self.config.data_dir, "DATA/wav/", path)
+                    yield key, {
+                        "path": path,
+                        "audio": path,
+                        "sysID": sysID,
+                        "uttID": uttID,
+                        "rating": rating,
+                        "age range": age,
+                        "listener id": listenrID,
+                        "gender": gender,
+                        "hearing impairment": hearingImpairement,
+                    }
+                if self.config.name == "ood_track":
+                    sysID, uttID = data[0].split("-")
+                    uttID = uttID.replace(".wav", "")
+                    if len(data) > 1:
+                        score = data[1]
+                    else:
+                        score = 999
+                    # Yields examples as (key, example) tuples
+                    path = os.path.join(self.config.data_dir, "DATA/wav/", data[0])
+                    yield key, {
+                        "path": path,
+                        "audio": path,
+                        "sysID": sysID,
+                        "uttID": uttID,
+                        "averaged rating": score,
+                    }
+                elif self.config.name == "ood_track_listeners":
+                    if len(data) > 1:
+                        rating = data[1]
+                        sysID, path, rating, _, listenerinfo = data
+                        _, age, listenrID, gender, _, _, hearingImpairement = (
+                            listenerinfo.split("_")
+                        )
+                    else:
+                        sysID, uttID = data[0].split("-")
+                        uttID = uttID.replace(".wav", "")
+                        path = data[0]
+                        rating = 999
+                        age = 999
+                        listenrID = 999
+                        gender = 999
+                    uttID = path.split("-")[-1]
+                    uttID = uttID.replace(".wav", "")
+                    path = os.path.join(self.config.data_dir, "DATA/wav/", path)
+                    yield key, {
+                        "path": path,
+                        "audio": path,
+                        "sysID": sysID,
+                        "uttID": uttID,
+                        "rating": rating,
+                        "age range": age,
+                        "listener id": listenrID,
+                        "gender": gender,
+                        "hearing impairment": hearingImpairement,
+                    }
+                if self.config.name == "ood_track_unlabeled":
+                    sysID, uttID = data[0].strip().split("-")
+                    uttID = uttID.replace(".wav", "")
+                    # Yields examples as (key, example) tuples
+                    path = os.path.join(
+                        self.config.data_dir, "DATA/wav/", data[0].strip()
+                    )
+                    yield key, {
+                        "path": path,
+                        "audio": path,
+                        "sysID": sysID,
+                        "uttID": uttID,
+                    }