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@@ -33,10 +33,10 @@ SpeechBrain. For a better experience, we encourage you to learn more about
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  ## Pipeline description
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  This ASR system is composed of 3 different but linked blocks:
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- 1. Tokenizer (unigram) that transforms words into subword units and trained with
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  the train transcriptions of LibriSpeech.
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- 2. Neural language model (Transformer LM) trained on the full 10M words dataset.
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- 3. Acoustic model made of a transformer encoder and a joint decoder with CTC +
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  transformer. Hence, the decoding also incorporates the CTC probabilities.
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@@ -75,7 +75,7 @@ The SpeechBrain team does not provide any warranty on the performance achieved b
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  year = {2021},
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  publisher = {GitHub},
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  journal = {GitHub repository},
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- howpublished = {\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\url{https://github.com/speechbrain/speechbrain}},
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  }
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  ```
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  ## Pipeline description
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  This ASR system is composed of 3 different but linked blocks:
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+ - Tokenizer (unigram) that transforms words into subword units and trained with
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  the train transcriptions of LibriSpeech.
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+ - Neural language model (Transformer LM) trained on the full 10M words dataset.
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+ - Acoustic model made of a transformer encoder and a joint decoder with CTC +
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  transformer. Hence, the decoding also incorporates the CTC probabilities.
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  year = {2021},
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  publisher = {GitHub},
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  journal = {GitHub repository},
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+ howpublished = {\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\url{https://github.com/speechbrain/speechbrain}},
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  }
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  ```
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