60 lines
1.9 KiB
Python
60 lines
1.9 KiB
Python
# Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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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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def __levenshtein(a, b):
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"""Calculates the Levenshtein distance between two sequences."""
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n, m = len(a), len(b)
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if n > m:
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# Make sure n <= m, to use O(min(n,m)) space
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a, b = b, a
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n, m = m, n
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current = list(range(n + 1))
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for i in range(1, m + 1):
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previous, current = current, [i] + [0] * n
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for j in range(1, n + 1):
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add, delete = previous[j] + 1, current[j - 1] + 1
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change = previous[j - 1]
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if a[j - 1] != b[i - 1]:
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change = change + 1
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current[j] = min(add, delete, change)
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return current[n]
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def word_error_rate(hypotheses, references):
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"""Computes average Word Error Rate (WER) between two text lists."""
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scores = 0
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words = 0
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len_diff = len(references) - len(hypotheses)
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if len_diff > 0:
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raise ValueError("Uneqal number of hypthoses and references: "
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"{0} and {1}".format(len(hypotheses), len(references)))
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elif len_diff < 0:
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hypotheses = hypotheses[:len_diff]
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for h, r in zip(hypotheses, references):
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h_list = h.split()
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r_list = r.split()
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words += len(r_list)
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scores += __levenshtein(h_list, r_list)
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if words!=0:
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wer = 1.0*scores/words
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else:
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wer = float('inf')
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return wer, scores, words
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