uploading code

.gitattributes

@@ -52,3 +52,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.jpg filter=lfs diff=lfs merge=lfs -text
 *.jpeg filter=lfs diff=lfs merge=lfs -text
 *.webp filter=lfs diff=lfs merge=lfs -text
+subesco.tar.gz filter=lfs diff=lfs merge=lfs -text

bn_emotion_speech_corpus.py

@@ -0,0 +1,73 @@
+import datasets
+
+_CITATION = """\
+@dataset{sadia_sultana_2021_4526477,
+  author       = {Sadia Sultana},
+  title        = {SUST Bangla Emotional Speech Corpus (SUBESCO)},
+  month        = feb,
+  year         = 2021,
+  note         = {{This database was created as a part of PhD thesis 
+                   project of the author Sadia Sultana. It was
+                   designed and developed by the author in the
+                   Department of Computer Science and Engineering  of
+                   Shahjalal University of Science and Technology.
+                   Financial grant was supported by the university.
+                   If you use the dataset please cite SUBESCO and the
+                   corresponding academic journal publication in Plos
+                   One.}},
+  publisher    = {Zenodo},
+  version      = {version - 1.1},
+  doi          = {10.5281/zenodo.4526477},
+  url          = {https://doi.org/10.5281/zenodo.4526477}
+}
+"""
+
+_DESCRIPTION = """\
+SUST Bangla Emotional Speech Coropus Dataset
+"""
+_HOMEPAGE = "https://huggingface.co/datasets/sustcsenlp/SUBESCO"
+
+_LICENSE = ""
+
+#_REPO = "https://huggingface.co/datasets/sustcsenlp/SUBESCO/resolve/main/corpus/speech/subesco.tar.gz"
+
+class AudioSet(datasets.GeneratorBasedBuilder):
+    """"""
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    'text': datasets.Value("string"),
+                    "audio": datasets.Audio(sampling_rate=16000),
+                }
+            ),
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        audio_archive = dl_manager.download("https://huggingface.co/datasets/sustcsenlp/bn_emotion_speech_corpus/resolve/main/subesco.tar.gz")
+        audio_iters = dl_manager.iter_archive(audio_archive)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "audios": audio_iters
+                }
+            ),
+        ]
+
+    def _generate_examples(self, audios):
+        """This function returns the examples in the raw (text) form."""
+        idx = 0
+        for filepath, audio in audios:
+            description = filepath.split('/')[-1][:-4]
+            description = description.replace('_', ' ')
+            yield idx, {
+                "audio": {"path": filepath, "bytes": audio.read()},
+                "text": description,
+            }
+            idx += 1