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| -rw-r--r-- | readme.md | 2 | ||||
| -rw-r--r-- | swr2_asr/loss_scores.py | 2 |
2 files changed, 2 insertions, 2 deletions
@@ -1,4 +1,4 @@ -# SWR2-ACR +# SWR2-ASR Automatic speech recognition model for the seminar spoken word recogniton 2 (SWR2) in the summer term 2023. diff --git a/swr2_asr/loss_scores.py b/swr2_asr/loss_scores.py index ef37b0a..63c8a8f 100644 --- a/swr2_asr/loss_scores.py +++ b/swr2_asr/loss_scores.py @@ -12,7 +12,7 @@ def _levenshtein_distance(ref, hyp): between two sequences. Informally, the levenshtein disctance is defined as the minimum number of single-character edits (substitutions, insertions or deletions) required to change one word into the other. We can naturally - extend the edits to word level when calculate levenshtein disctance for + extend the edits to word level when calculating levenshtein disctance for two sentences. """ len_ref = len(ref) |