Update superb.py

superb.py

@@ -143,7 +143,7 @@ class Superb(datasets.GeneratorBasedBuilder):
             ),
             supervised_keys=("file", "text"),
             url="http://www.openslr.org/12",
-            data_url="http://www.openslr.org/resources/12/",
+            data_url="https://huggingface.co/datasets/lhoestq/superb-asr/resolve/main/",
         ),
         SuperbConfig(
             name="ks",
@@ -221,7 +221,7 @@ class Superb(datasets.GeneratorBasedBuilder):
             ),
             supervised_keys=None,
             url="https://fluent.ai/fluent-speech-commands-a-dataset-for-spoken-language-understanding-research/",
-            data_url="http://fluent.ai:2052/jf8398hf30f0381738rucj3828chfdnchs.tar.gz",
+            data_url="https://huggingface.co/datasets/lhoestq/fluent-speech-corpus/resolve/main/fluent_speech_commands_dataset.zip",
         ),
         SuperbConfig(
             name="si",
@@ -271,7 +271,7 @@ class Superb(datasets.GeneratorBasedBuilder):
             ),  # TODO
             supervised_keys=None,  # TODO
             url="https://github.com/ftshijt/LibriMix",
-            data_url="https://huggingface.co/datasets/superb/superb-data/resolve/main/sd/{split}/{filename}",
+            data_url="https://huggingface.co/datasets/lhoestq/LibriMix-sd/resolve/main/{split}/{filename}",
         ),
         SuperbConfig(
             name="er",
@@ -294,42 +294,6 @@ class Superb(datasets.GeneratorBasedBuilder):
         ),
     ]
 
-    @property
-    def manual_download_instructions(self):
-        if self.config.name == "si":
-            return textwrap.dedent(
-                """
-            Please download the VoxCeleb dataset using the following script,
-            which should create `VoxCeleb1/wav/id*` directories for both train and test speakers`:
-            ```
-            mkdir VoxCeleb1
-            cd VoxCeleb1
-
-            wget https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partaa
-            wget https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partab
-            wget https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partac
-            wget https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_dev_wav_partad
-            cat vox1_dev* > vox1_dev_wav.zip
-            unzip vox1_dev_wav.zip
-
-            wget https://thor.robots.ox.ac.uk/~vgg/data/voxceleb/vox1a/vox1_test_wav.zip
-            unzip vox1_test_wav.zip
-
-            # download the official SUPERB train-dev-test split
-            wget https://raw.githubusercontent.com/s3prl/s3prl/master/s3prl/downstream/voxceleb1/veri_test_class.txt
-            ```"""
-            )
-        elif self.config.name == "er":
-            return textwrap.dedent(
-                """
-            Please download the IEMOCAP dataset after submitting the request form here:
-            https://sail.usc.edu/iemocap/iemocap_release.htm
-            Having downloaded the dataset you can extract it with `tar -xvzf IEMOCAP_full_release.tar.gz`
-            which should create a folder called `IEMOCAP_full_release`
-            """
-            )
-        return None
-
     def _info(self):
         return datasets.DatasetInfo(
             description=_DESCRIPTION,
@@ -390,24 +354,28 @@ class Superb(datasets.GeneratorBasedBuilder):
                 ),
             ]
         elif self.config.name == "si":
-            manual_dir = os.path.abspath(os.path.expanduser(dl_manager.manual_dir))
+            archive_path = (
+                dl_manager.download_and_extract("https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox1/vox1_dev_wav.zip"),
+                dl_manager.download_and_extract("https://huggingface.co/datasets/ProgramComputer/voxceleb/resolve/main/vox1/vox1_test_wav.zip"),
+                dl_manager.download_and_extract("https://raw.githubusercontent.com/s3prl/s3prl/master/s3prl/downstream/voxceleb1/veri_test_class.txt"),
+            )
             return [
                 datasets.SplitGenerator(
                     name=datasets.Split.TRAIN,
-                    gen_kwargs={"archive_path": manual_dir, "split": 1},
+                    gen_kwargs={"archive_path": archive_path, "split": 1},
                 ),
                 datasets.SplitGenerator(
                     name=datasets.Split.VALIDATION,
-                    gen_kwargs={"archive_path": manual_dir, "split": 2},
+                    gen_kwargs={"archive_path": archive_path, "split": 2},
                 ),
-                datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"archive_path": manual_dir, "split": 3}),
+                datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"archive_path": archive_path, "split": 3}),
             ]
         elif self.config.name == "sd":
             splits = ["train", "dev", "test"]
             _DL_URLS = {
                 split: {
                     filename: self.config.data_url.format(split=split, filename=filename)
-                    for filename in ["reco2dur", "segments", "utt2spk", "wav.zip"]
+                    for filename in ["reco2dur", "segments", "utt2spk", "mix_both.zip"]
                 }
                 for split in splits
             }
@@ -419,11 +387,13 @@ class Superb(datasets.GeneratorBasedBuilder):
                 for split in splits
             ]
         elif self.config.name == "er":
-            manual_dir = os.path.abspath(os.path.expanduser(dl_manager.manual_dir))
+            archive_path = (
+                dl_manager.download_and_extract("https://huggingface.co/datasets/lhoestq/IEMOCAP_full_release/resolve/main/IEMOCAP_full_release.zip")
+            )
             return [
                 datasets.SplitGenerator(
                     name=f"session{i}",
-                    gen_kwargs={"archive_path": manual_dir, "split": i},
+                    gen_kwargs={"archive_path": archive_path, "split": i},
                 )
                 for i in range(1, 6)
             ]
@@ -465,14 +435,13 @@ class Superb(datasets.GeneratorBasedBuilder):
                     label = "_unknown_"
                 yield key, {"file": audio_file, "audio": audio_file, "label": label}
         elif self.config.name == "ic":
-            root_path = os.path.join(archive_path, "fluent_speech_commands_dataset")
-            csv_path = os.path.join(root_path, "data", f"{split}_data.csv")
+            csv_path = os.path.join(archive_path, "data", f"{split}_data.csv")
             with open(csv_path, encoding="utf-8") as csv_file:
                 csv_reader = csv.reader(csv_file, delimiter=",", skipinitialspace=True)
                 next(csv_reader)
                 for row in csv_reader:
                     key, file_path, speaker_id, text, action, object_, location = row
-                    audio_path = os.path.join(root_path, file_path)
+                    audio_path = os.path.join(archive_path, file_path)
                     yield key, {
                         "file": audio_path,
                         "audio": audio_path,
@@ -483,20 +452,22 @@ class Superb(datasets.GeneratorBasedBuilder):
                         "location": location,
                     }
         elif self.config.name == "si":
-            wav_path = os.path.join(archive_path, "wav")
-            splits_path = os.path.join(archive_path, "veri_test_class.txt")
+            *archives_dirs, splits_path = archive_path
             with open(splits_path, "r", encoding="utf-8") as f:
                 for key, line in enumerate(f):
                     split_id, file_path = line.strip().split(" ")
                     if int(split_id) != split:
                         continue
                     speaker_id = file_path.split("/")[0]
-                    audio_path = os.path.join(wav_path, file_path)
-                    yield key, {
-                        "file": audio_path,
-                        "audio": audio_path,
-                        "label": speaker_id,
-                    }
+                    for archive_dir in archives_dirs: # in one or the other
+                        wav_path = os.path.join(archive_dir, "wav")
+                        audio_path = os.path.join(wav_path, file_path)
+                        if os.path.exists(audio_path):
+                            yield key, {
+                                "file": audio_path,
+                                "audio": audio_path,
+                                "label": speaker_id,
+                            }
         elif self.config.name == "sd":
             data = SdData(archive_path)
             args = SdArgs()
@@ -556,7 +527,7 @@ class SdData:
         """Load sd data."""
         self.segments = self._load_segments_rechash(data_dir["segments"])
         self.utt2spk = self._load_utt2spk(data_dir["utt2spk"])
-        self.wavs = self._load_wav_zip(data_dir["wav.zip"])
+        self.wavs = self._load_wav_zip(data_dir["mix_both.zip"])
         self.reco2dur = self._load_reco2dur(data_dir["reco2dur"])
 
     def _load_segments_rechash(self, segments_file):
@@ -574,7 +545,7 @@ class SdData:
 
     def _load_wav_zip(self, wav_zip):
         """Return dictionary { rec: wav_rxfilename }."""
-        wav_dir = os.path.join(wav_zip, "wav")
+        wav_dir = os.path.join(wav_zip, "mix_both")
         return {
             os.path.splitext(filename)[0]: os.path.join(wav_dir, filename) for filename in sorted(os.listdir(wav_dir))
         }