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Update tamil_eng_data.py

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  1. tamil_eng_data.py +72 -13
tamil_eng_data.py CHANGED
@@ -12,33 +12,93 @@
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  # See the License for the specific language governing permissions and
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  # limitations under the License.
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- """Simple sentences Dataset - contains 90 mins of speech data"""
 
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- import csv
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  import json
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  import os
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  import datasets
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  _CITATION = """\
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- @misc{simpledata_1,
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- title = {Whisper model for tamil-to-eng translation},
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- publisher = {Achitha},
 
 
 
 
 
 
 
 
 
 
 
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  year = {2022},
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  }
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- @misc{simpledata_2,
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- title = {Fine-tuning whisper model},
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- publisher = {Achitha},
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  year = {2022},
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  }
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  """
 
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  _DESCRIPTION = """\
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- The data contains roughly one and half hours of audio and transcripts in Tamil language.
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  """
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  _HOMEPAGE = ""
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- _LICENSE = "MIT"
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  _METADATA_URLS = {
@@ -51,8 +111,8 @@ _URLS = {
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  }
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- class simple_data(datasets.GeneratorBasedBuilder):
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-
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  VERSION = datasets.Version("1.1.0")
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  def _info(self):
@@ -62,7 +122,6 @@ class simple_data(datasets.GeneratorBasedBuilder):
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  "path": datasets.Value("string"),
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  "sentence": datasets.Value("string"),
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  "length": datasets.Value("float")
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-
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  }
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  )
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  return datasets.DatasetInfo(
 
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  # See the License for the specific language governing permissions and
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  # limitations under the License.
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+ """Filtered Tamil ASR corpus collected from common_voice 11, fleurs, openslr65, openslr127 and ucla corpora filtered for duration between 5 - 25 secs"""
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+
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  import json
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  import os
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  import datasets
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  _CITATION = """\
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+ @misc{mile_1,
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+ doi = {10.48550/ARXIV.2207.13331},
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+ url = {https://arxiv.org/abs/2207.13331},
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+ author = {A, Madhavaraj and Pilar, Bharathi and G, Ramakrishnan A},
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+ title = {Subword Dictionary Learning and Segmentation Techniques for Automatic Speech Recognition in Tamil and Kannada},
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+ publisher = {arXiv},
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+ year = {2022},
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+ }
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+ @misc{mile_2,
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+ doi = {10.48550/ARXIV.2207.13333},
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+ url = {https://arxiv.org/abs/2207.13333},
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+ author = {A, Madhavaraj and Pilar, Bharathi and G, Ramakrishnan A},
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+ title = {Knowledge-driven Subword Grammar Modeling for Automatic Speech Recognition in Tamil and Kannada},
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+ publisher = {arXiv},
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  year = {2022},
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  }
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+ @inproceedings{he-etal-2020-open,
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+ title = {{Open-source Multi-speaker Speech Corpora for Building Gujarati, Kannada, Malayalam, Marathi, Tamil and Telugu Speech Synthesis Systems}},
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+ author = {He, Fei and Chu, Shan-Hui Cathy and Kjartansson, Oddur and Rivera, Clara and Katanova, Anna and Gutkin, Alexander and Demirsahin, Isin and Johny, Cibu and Jansche, Martin and Sarin, Supheakmungkol and Pipatsrisawat, Knot},
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+ booktitle = {Proceedings of The 12th Language Resources and Evaluation Conference (LREC)},
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+ month = may,
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+ year = {2020},
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+ address = {Marseille, France},
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+ publisher = {European Language Resources Association (ELRA)},
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+ pages = {6494--6503},
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+ url = {https://www.aclweb.org/anthology/2020.lrec-1.800},
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+ ISBN = "{979-10-95546-34-4},
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+ }
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+ @misc{https://doi.org/10.48550/arxiv.2211.09536,
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+ doi = {10.48550/ARXIV.2211.09536},
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+
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+ url = {https://arxiv.org/abs/2211.09536},
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+
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+ author = {Kumar, Gokul Karthik and S, Praveen and Kumar, Pratyush and Khapra, Mitesh M. and Nandakumar, Karthik},
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+
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+ keywords = {Computation and Language (cs.CL), Machine Learning (cs.LG), Sound (cs.SD), Audio and Speech Processing (eess.AS), FOS: Computer and information sciences, FOS: Computer and information sciences, FOS: Electrical engineering, electronic engineering, information engineering, FOS: Electrical engineering, electronic engineering, information engineering},
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+
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+ title = {Towards Building Text-To-Speech Systems for the Next Billion Users},
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+
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+ publisher = {arXiv},
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+
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  year = {2022},
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+
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+ copyright = {arXiv.org perpetual, non-exclusive license}
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+ }
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+ @inproceedings{commonvoice:2020,
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+ 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.},
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+ title = {Common Voice: A Massively-Multilingual Speech Corpus},
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+ booktitle = {Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020)},
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+ pages = {4211--4215},
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+ year = 2020
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+ }
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+ @misc{https://doi.org/10.48550/arxiv.2205.12446,
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+ doi = {10.48550/ARXIV.2205.12446},
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+
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+ url = {https://arxiv.org/abs/2205.12446},
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+
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+ author = {Conneau, Alexis and Ma, Min and Khanuja, Simran and Zhang, Yu and Axelrod, Vera and Dalmia, Siddharth and Riesa, Jason and Rivera, Clara and Bapna, Ankur},
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+
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+ keywords = {Computation and Language (cs.CL), Machine Learning (cs.LG), Sound (cs.SD), Audio and Speech Processing (eess.AS), FOS: Computer and information sciences, FOS: Computer and information sciences, FOS: Electrical engineering, electronic engineering, information engineering, FOS: Electrical engineering, electronic engineering, information engineering},
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+
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+ title = {FLEURS: Few-shot Learning Evaluation of Universal Representations of Speech},
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+
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+ publisher = {arXiv},
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+
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+ year = {2022},
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+
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+ copyright = {Creative Commons Attribution 4.0 International}
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  }
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  """
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+
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  _DESCRIPTION = """\
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+ The corpus contains roughly 1000 hours of audio and trasncripts in Tamil language. The transcripts have beedn de-duplicated using exact match deduplication.
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  """
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  _HOMEPAGE = ""
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+ _LICENSE = "https://creativecommons.org/licenses/"
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  _METADATA_URLS = {
 
111
 
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  }
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+ class TamilASRCorpus(datasets.GeneratorBasedBuilder):
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+ """Tamil ASR Corpus contains transcribed speech corpus for training ASR systems for Tamil language."""
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  VERSION = datasets.Version("1.1.0")
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  def _info(self):
 
122
  "path": datasets.Value("string"),
123
  "sentence": datasets.Value("string"),
124
  "length": datasets.Value("float")
 
125
  }
126
  )
127
  return datasets.DatasetInfo(