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README.md
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@@ -57,10 +57,16 @@ With streaming, the results with different chunk sizes on the test split are the
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| | full | cs=32 (1280ms) | 24 (960ms) | 16 (640ms) | 12 (480ms) | 8 (320ms) |
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|:-----:|:------:|:------:|:------:|:------:|:------:|:------:|
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| full | 11.00% | - | - | - | - | - |
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| 16 | - | - | - |
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| 8 | - | - | 11.50% |
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| 4 | - | 11.40% | 11.53% |
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| 2 | - | 11.46% | 11.67% |
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## Pipeline description
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| | full | cs=32 (1280ms) | 24 (960ms) | 16 (640ms) | 12 (480ms) | 8 (320ms) |
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|:-----:|:------:|:------:|:------:|:------:|:------:|:------:|
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| full | 11.00% | - | - | - | - | - |
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| 16 | - | - | - | 11.70% | 11.84% | 12.14% |
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| 8 | - | - | 11.50% | 11.72% | 11.88% | 12.28% |
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| 4 | - | 11.40% | 11.53% | 11.81% | 12.03% | 12.64% |
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| 2 | - | 11.46% | 11.67% | 12.03% | 12.43% | 13.25% |
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| 1\* | - | 11.59% | TBD | TBD | TBD | TBD |
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(\*: model was never explicitly trained with this setting)
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When comparing configurations, bear in mind that the utterances of the test set are of a finite length.
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All WER values were evaluated using [this script](https://gist.github.com/asumagic/66aaf43156c31866cf2ebcffda46ea01) (until we integrate a nicer way to evaluate streaming WER in different conditions).
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## Pipeline description
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