Update README.md
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README.md
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@@ -45,7 +45,7 @@ ds = load_dataset("common_voice", "fr", split="test", cache_dir="./data/fr")
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chars_to_ignore_regex = '[
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def map_to_array(batch):
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speech, _ = torchaudio.load(batch["path"])
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batch["speech"] = resampler.forward(speech.squeeze(0)).numpy()
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@@ -79,7 +79,9 @@ print(wer.compute(predictions=result["predicted"], references=result["target"]))
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## Testing
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All the Common Voice `Test` dataset (15763 files) were used for testing.
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Results:
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WER=20.89%
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SER=77.56%
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chars_to_ignore_regex = '[\\,\\?\\.\\!\\-\\;\\:\\"\\“\\%\\‘\\”\\�\\‘\\’\\’\\’\\‘\\…\\·\\!\\ǃ\\?\\«\\‹\\»\\›“\\”\\\\ʿ\\ʾ\\„\\∞\\\\|\\.\\,\\;\\:\\*\\—\\–\\─\\―\\_\\/\\:\\ː\\;\\,\\=\\«\\»\\→]'
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def map_to_array(batch):
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speech, _ = torchaudio.load(batch["path"])
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batch["speech"] = resampler.forward(speech.squeeze(0)).numpy()
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## Testing
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All the Common Voice `Test` dataset (15763 files) were used for testing.
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Results:
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WER=20.89%
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SER=77.56%
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