back to previous version with bundleurltemplate ha hardcoded to 'bn'

CommonVoiceBangla.py → common_voice_bn.py

@@ -1,60 +1,46 @@
-# coding=utf-8
-# Copyright 2022 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.
-""" Common Voice Dataset"""
-
-
 import csv
 import os
 import urllib
-import shutil
+
+
+import datasets
+from datasets.utils.py_utils import size_str
+
+
 import datasets
 import requests
 from datasets.utils.py_utils import size_str
 from huggingface_hub import HfApi, HfFolder
 
-from .languages import LANGUAGES
+# from .languages import LANGUAGES
+#Used to get tar.gz file from mozilla website
 from .release_stats import STATS
 
-_CITATION = """\
-@inproceedings{commonvoice:2020,
-  author = {Ardila, R. and Branson, M. and Davis, K. and Henretty, M. and Kohler, M. and Meyer, J. and Morais, R. and Saunders, L. and Tyers, F. M. and Weber, G.},
-  title = {Common Voice: A Massively-Multilingual Speech Corpus},
-  booktitle = {Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020)},
-  pages = {4211--4215},
-  year = 2020
-}
-"""
 
-_HOMEPAGE = "https://commonvoice.mozilla.org/bn/datasets"
+
+#Hard Links
+
+_HOMEPAGE = "https://commonvoice.mozilla.org/en/datasets"
 
 _LICENSE = "https://creativecommons.org/publicdomain/zero/1.0/"
 
 _API_URL = "https://commonvoice.mozilla.org/api/v1"
 
 
+
+
+
 class CommonVoiceConfig(datasets.BuilderConfig):
     """BuilderConfig for CommonVoice."""
 
     def __init__(self, name, version, **kwargs):
-        self.language = kwargs.pop("language", None)
-        self.release_date = kwargs.pop("release_date", None)
-        self.num_clips = kwargs.pop("num_clips", None)
-        self.num_speakers = kwargs.pop("num_speakers", None)
-        self.validated_hr = kwargs.pop("validated_hr", None)
-        self.total_hr = kwargs.pop("total_hr", None)
-        self.size_bytes = kwargs.pop("size_bytes", None)
+        self.language = "bn"  # kwargs.pop("language", None)
+        self.release_date = "2022-04-27"  # kwargs.pop("release_date", None)
+        self.num_clips = 231120  # kwargs.pop("num_clips", None)
+        self.num_speakers = 19863  # kwargs.pop("num_speakers", None)
+        self.validated_hr = 56.61  # kwargs.pop("validated_hr", None)
+        self.total_hr = 399.47  # kwargs.pop("total_hr", None)
+        self.size_bytes = 8262390506  # kwargs.pop("size_bytes", None)
         self.size_human = size_str(self.size_bytes)
         description = (
             f"Common Voice speech to text dataset in {self.language} released on {self.release_date}. "
@@ -71,31 +57,33 @@ class CommonVoiceConfig(datasets.BuilderConfig):
 
 
 class CommonVoice(datasets.GeneratorBasedBuilder):
+    #DEFAULT_CONFIG_NAME = "en"
     DEFAULT_CONFIG_NAME = "bn"
     DEFAULT_WRITER_BATCH_SIZE = 1000
 
     BUILDER_CONFIGS = [
         CommonVoiceConfig(
-            name=lang,
-            version=STATS["version"],
-            language=LANGUAGES[lang],
-            release_date=STATS["date"],
-            num_clips=lang_stats["clips"],
-            num_speakers=lang_stats["users"],
-            validated_hr=float(lang_stats["validHrs"]),
-            total_hr=float(lang_stats["totalHrs"]),
-            size_bytes=int(lang_stats["size"]),
+            name="bn"#lang,
+            version= '9.0.0' #STATS["version"],
+            language= "Bengali" #LANGUAGES[lang],
+            release_date= "2022-04-27" #STATS["date"],
+            num_clips= 231120 #lang_stats["clips"],
+            num_speakers= 19863 #lang_stats["users"],
+            validated_hr= float(56.61) #float(lang_stats["validHrs"]),
+            total_hr= float(399.47) #float(lang_stats["totalHrs"]),
+            size_bytes= int(8262390506) #int(lang_stats["size"]),
         )
-        for lang, lang_stats in STATS["locales"].items()
+        #for lang, lang_stats in STATS["locales"].items()
     ]
 
     def _info(self):
-        total_languages = len(STATS["locales"])
-        total_valid_hours = STATS["totalValidHrs"]
+        # total_languages = len(STATS["locales"])
+        # total_valid_hours = STATS["totalValidHrs"]
+        total_languages = 1 #len(STATS["locales"])
+        total_valid_hours = float(399.47) #STATS["totalValidHrs"]
         description = (
-            "Common Voice is Mozilla's initiative to help teach machines how real people speak. "
-            f"The dataset currently consists of {total_valid_hours} validated hours of speech "
-            f" in {total_languages} languages, but more voices and languages are always added."
+            "Common Voice Bangla is bengali AI's initiative to help teach machines how real people speak in Bangla. "
+            f"The dataset is for initial training of a general speech recognition model for Bangla."
         )
         features = datasets.Features(
             {
@@ -108,7 +96,7 @@ class CommonVoice(datasets.GeneratorBasedBuilder):
                 "age": datasets.Value("string"),
                 "gender": datasets.Value("string"),
                 "accent": datasets.Value("string"),
-                "locale": datasets.Value("string"),
+                "locale": 'bn',
                 "segment": datasets.Value("string"),
             }
         )
@@ -117,22 +105,26 @@ class CommonVoice(datasets.GeneratorBasedBuilder):
             description=description,
             features=features,
             supervised_keys=None,
-            homepage=_HOMEPAGE,
+            # homepage=_HOMEPAGE,
             license=_LICENSE,
-            citation=_CITATION,
-            version=self.config.version,
-            # task_templates=[
-            #     AutomaticSpeechRecognition(audio_file_path_column="path", transcription_column="sentence")
-            # ],
+            # citation=_CITATION,
+            version=self.config.version,            
+            #task_templates=[
+            #    AutomaticSpeechRecognition(audio_file_path_column="path", transcription_column="sentence")
+            #],
         )
 
+
     def _get_bundle_url(self, locale, url_template):
         # path = encodeURIComponent(path)
-        path = url_template.replace("{locale}", locale)
+        # path = url_template.replace("{locale}", locale)
+        path = url_template
         path = urllib.parse.quote(path.encode("utf-8"), safe="~()*!.'")
         # use_cdn = self.config.size_bytes < 20 * 1024 * 1024 * 1024
         # response = requests.get(f"{_API_URL}/bucket/dataset/{path}/{use_cdn}", timeout=10.0).json()
-        response = requests.get(f"{_API_URL}/bucket/dataset/{path}", timeout=10.0).json()
+        response = requests.get(
+            f"{_API_URL}/bucket/dataset/{path}", timeout=10.0
+        ).json()
         return response["url"]
 
     def _log_download(self, locale, bundle_version, auth_token):
@@ -156,8 +148,12 @@ class CommonVoice(datasets.GeneratorBasedBuilder):
         dl_manager.download_config.ignore_url_params = True
 
         self._log_download(self.config.name, bundle_version, hf_auth_token)
-        archive_path = dl_manager.download(self._get_bundle_url(self.config.name, bundle_url_template))
-        local_extracted_archive = dl_manager.extract(archive_path) if not dl_manager.is_streaming else None
+        archive_path = dl_manager.download(
+            self._get_bundle_url(self.config.name, bundle_url_template)
+        )
+        local_extracted_archive = (
+            dl_manager.extract(archive_path) if not dl_manager.is_streaming else None
+        )
 
         if self.config.version < datasets.Version("5.0.0"):
             path_to_data = ""
@@ -165,16 +161,21 @@ class CommonVoice(datasets.GeneratorBasedBuilder):
             path_to_data = "/".join([bundle_version, self.config.name])
         path_to_clips = "/".join([path_to_data, "clips"]) if path_to_data else "clips"
 
-        
+        #we provide our custom csvs with the huggingface repo so,
+        path_to_tsvs = "/" + "bengali_ai_tsv" + "/"
+
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 gen_kwargs={
                     "local_extracted_archive": local_extracted_archive,
                     "archive_iterator": dl_manager.iter_archive(archive_path),
-                    "metadata_filepath": "/data/train.tsv",
+                    #"metadata_filepath": "/".join([path_to_data, "train.tsv"])
+                    # if path_to_data
+                    # else "train.tsv",
+                    #custom train.tsv
+                    "metadata_filepath": "/".join([path_to_tsvs, "train.tsv"]),
                     "path_to_clips": path_to_clips,
-                    "mode":"train",
                 },
             ),
             datasets.SplitGenerator(
@@ -182,9 +183,12 @@ class CommonVoice(datasets.GeneratorBasedBuilder):
                 gen_kwargs={
                     "local_extracted_archive": local_extracted_archive,
                     "archive_iterator": dl_manager.iter_archive(archive_path),
-                    "metadata_filepath": "/".join([path_to_data, "test.tsv"]) if path_to_data else "test.tsv",
+                    #"metadata_filepath": "/".join([path_to_data, "test.tsv"])
+                    # if path_to_data
+                    # else "test.tsv",
+                    #custom test.tsv
+                    "metadata_filepath": "/".join([path_to_tsvs, "test.tsv"]),
                     "path_to_clips": path_to_clips,
-                    "mode":"test",
                 },
             ),
             datasets.SplitGenerator(
@@ -192,88 +196,71 @@ class CommonVoice(datasets.GeneratorBasedBuilder):
                 gen_kwargs={
                     "local_extracted_archive": local_extracted_archive,
                     "archive_iterator": dl_manager.iter_archive(archive_path),
-                    "metadata_filepath": "/".join([path_to_data, "dev.tsv"]) if path_to_data else "dev.tsv",
+                    # "metadata_filepath": "/".join([path_to_data, "dev.tsv"])
+                    # if path_to_data
+                    # else "dev.tsv",
+                    #custom test.tsv
+                    "metadata_filepath": "/".join([path_to_tsvs, "dev.tsv"]),
                     "path_to_clips": path_to_clips,
-                    "mode":"dev",
                 },
             ),
         ]
 
+
+
     def _generate_examples(
         self,
         local_extracted_archive,
         archive_iterator,
         metadata_filepath,
         path_to_clips,
-        mode
     ):
         """Yields examples."""
         data_fields = list(self._info().features.keys())
         metadata = {}
         metadata_found = False
-        if mode in ["dev","test"]:
-            for path, f in archive_iterator:
-                if path == metadata_filepath:
-                    metadata_found = True
-                    lines = (line.decode("utf-8") for line in f)
-                    reader = csv.DictReader(lines, delimiter="\t", quoting=csv.QUOTE_NONE)
-                    for row in reader:
-                        # set absolute path for mp3 audio file
-                        if not row["path"].endswith(".mp3"):
-                            row["path"] += ".mp3"
-                        row["path"] = os.path.join(path_to_clips, row["path"])
-                        # accent -> accents in CV 8.0
-                        if "accents" in row:
-                            row["accent"] = row["accents"]
-                            del row["accents"]
-                        # if data is incomplete, fill with empty values
-                        for field in data_fields:
-                            if field not in row:
-                                row[field] = ""
-                        metadata[row["path"]] = row
-                elif path.startswith(path_to_clips):
-                    assert metadata_found, "Found audio clips before the metadata TSV file."
-                    if not metadata:
-                        break
-                    if path in metadata:
-                        result = metadata[path]
-                        # set the audio feature and the path to the extracted file
-                        path = os.path.join(local_extracted_archive, path) if local_extracted_archive else path
-                        result["audio"] = {"path": path, "bytes": f.read()}
-                        # set path to None if the audio file doesn't exist locally (i.e. in streaming mode)
-                        result["path"] = path if local_extracted_archive else None
-
-                        yield path, result
-        else:
-            metadata_found = True
-            with open(metadata_filepath, "rb") as file_obj:
-                lines = (line.decode("utf-8") for line in file_obj)
-            reader = csv.DictReader(lines, delimiter="\t", quoting=csv.QUOTE_NONE)
-            for row in reader:
-                # set absolute path for mp3 audio file
-                if not row["path"].endswith(".mp3"):
-                    row["path"] += ".mp3"
-                row["path"] = os.path.join(path_to_clips, row["path"])
-                # accent -> accents in CV 8.0
-                if "accents" in row:
-                    row["accent"] = row["accents"]
-                    del row["accents"]
-                # if data is incomplete, fill with empty values
-                for field in data_fields:
-                    if field not in row:
-                        row[field] = ""
-                metadata[row["path"]] = row
-            for path, f in archive_iterator:
-                if path.startswith(path_to_clips):
-                    assert metadata_found, "Found audio clips before the metadata TSV file."
-                    if not metadata:
-                        break
-                    if path in metadata:
-                        result = metadata[path]
-                        # set the audio feature and the path to the extracted file
-                        path = os.path.join(local_extracted_archive, path) if local_extracted_archive else path
-                        result["audio"] = {"path": path, "bytes": f.read()}
-                        # set path to None if the audio file doesn't exist locally (i.e. in streaming mode)
-                        result["path"] = path if local_extracted_archive else None
-
-                        yield path, result
+        for path, f in archive_iterator:
+            if path == metadata_filepath:
+                metadata_found = True
+                lines = (line.decode("utf-8") for line in f)
+                reader = csv.DictReader(lines, delimiter="\t", quoting=csv.QUOTE_NONE)
+                for row in reader:
+                    # set absolute path for mp3 audio file
+                    if not row["path"].endswith(".mp3"):
+                        row["path"] += ".mp3"
+                    row["path"] = os.path.join(path_to_clips, row["path"])
+                    # accent -> accents in CV 8.0
+                    if "accents" in row:
+                        row["accent"] = row["accents"]
+                        del row["accents"]
+                    # if data is incomplete, fill with empty values
+                    for field in data_fields:
+                        if field not in row:
+                            row[field] = ""
+                    metadata[row["path"]] = row
+            elif path.startswith(path_to_clips):
+                assert metadata_found, "Found audio clips before the metadata TSV file."
+                if not metadata:
+                    break
+                if path in metadata:
+                    result = metadata[path]
+                    # set the audio feature and the path to the extracted file
+                    path = (
+                        os.path.join(local_extracted_archive, path)
+                        if local_extracted_archive
+                        else path
+                    )
+                    result["audio"] = {"path": path, "bytes": f.read()}
+                    # set path to None if the audio file doesn't exist locally (i.e. in streaming mode)
+                    result["path"] = path if local_extracted_archive else None
+
+                    yield path, result
+
+
+
+# 'bn': {'duration': 1438112808, 'reportedSentences': 693, 'buckets': {'dev': 7748, 'invalidated': 5844, 'other': 192522,
+# 'reported': 717, 'test': 7748, 'train': 14503, 'validated': 32754}, 'clips': 231120, 'splits': {'accent': {'': 1},
+# 'age': {'thirties': 0.02, 'twenties': 0.22, '': 0.72, 'teens': 0.04, 'fourties': 0},
+#  'gender': {'male': 0.24, '': 0.72, 'female': 0.04, 'other': 0}}, 'users': 19863, 'size': 8262390506,
+#  'checksum': '599a5f7c9e55a297928da390345a19180b279a1f013081e7255a657fc99f98d5', 'avgDurationSecs': 6.222,
+#   'validDurationSecs': 203807.316, 'totalHrs': 399.47, 'validHrs': 56.61},

release_stats.py

@@ -1,5 +1,5 @@
 STATS = {
-    "bundleURLTemplate": 'cv-corpus-9.0-2022-04-27/cv-corpus-9.0-2022-04-27-{locale}.tar.gz',
+    "bundleURLTemplate": "cv-corpus-9.0-2022-04-27/cv-corpus-9.0-2022-04-27-bn.tar.gz",
     "date": "2022-04-27",
     "name": "Common Voice Corpus 9.0",
     "multilingual": True,