зеркало из https://github.com/mozilla/DSAlign.git
Shrinking support during fine-alignment
This commit is contained in:
Tilman Kamp
Родитель
92f23253bb
Коммит
d2530ed745
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@ -97,14 +97,16 @@ def main(args):
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help='Mismatch score for Smith-Waterman alignment (default: -100)')
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align_group.add_argument('--align-gap-score', type=int, required=False, default=-100,
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help='Gap score for Smith-Waterman alignment (default: -100)')
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align_group.add_argument('--align-stretch-fraction', type=float, required=False, default=1,
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help='Length fraction of the fragment that it could get stretched for matching')
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align_group.add_argument('--align-shrink-fraction', type=float, required=False, default=0.1,
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help='Length fraction of the fragment that it could get shrinked during fine alignment')
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align_group.add_argument('--align-stretch-fraction', type=float, required=False, default=0.25,
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help='Length fraction of the fragment that it could get stretched during fine alignment')
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align_group.add_argument('--align-word-snap-factor', type=float, required=False, default=1.5,
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help='Priority factor for snapping matched texts to word boundaries '
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'(default: 1.5 - slightly snappy)')
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align_group.add_argument('--align-phrase-snap-factor', type=float, required=False, default=2.5,
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align_group.add_argument('--align-phrase-snap-factor', type=float, required=False, default=1.5,
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help='Priority factor for snapping matched texts to word boundaries '
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'(default: 2.5 - snappy)')
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'(default: 1.5 - snappy)')
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align_group.add_argument('--align-similarity-algo', type=str, required=False, default='wng',
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help='Similarity algorithm during fine-alignment - one of '
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'wng|editex|levenshtein|mra|hamming|jaro_winkler (default: wng)')
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@ -246,9 +248,6 @@ def main(args):
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logging.debug('Loading acoustic model from "%s", alphabet from "%s" and language model from "%s"...' %
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(output_graph_path, alphabet_path, lm_path))
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inference_time = 0.0
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offset = 0
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# Run VAD on the input file
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logging.debug("Transcribing VAD segments...")
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aggressiveness = int(args.audio_vad_aggressiveness) if args.audio_vad_aggressiveness else 3
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@ -354,7 +353,7 @@ def main(args):
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if algo in similarity_algos:
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return similarity_algos[algo](a, b)
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algo_impl = lambda aa, bb: None
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if algo == 'wng':
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if algo.lower() == 'wng':
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algo_impl = similarity_algos[algo] = lambda aa, bb: similarity(
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aa,
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bb,
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@ -370,14 +369,13 @@ def main(args):
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exit(1)
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return algo_impl(a, b)
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def get_similarities(a, b, gap_text, gap_meta, direction):
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def get_similarities(a, b, n, gap_text, gap_meta, direction):
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if direction < 0:
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a, b, gap_text, gap_meta = a[::-1], b[::-1], gap_text[::-1], gap_meta[::-1]
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n = min(len(gap_text), int(args.align_stretch_fraction * len(b)))
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similarities = list(map(
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lambda i: (args.align_word_snap_factor if gap_text[i] == ' ' else 1) *
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(args.align_phrase_snap_factor if gap_meta[i] is None else 1) *
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(phrase_similarity(args.align_similarity_algo, a, b + gap_text[:i])),
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lambda i: (args.align_word_snap_factor if gap_text[i + 1] == ' ' else 1) *
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(args.align_phrase_snap_factor if gap_meta[i + 1] is None else 1) *
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(phrase_similarity(args.align_similarity_algo, a, b + gap_text[1:i + 1])),
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range(n)))
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best = max((v, i) for i, v in enumerate(similarities))[1] if n > 0 else 0
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return best, similarities
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@ -386,25 +384,38 @@ def main(args):
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if index > 0:
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a = matched_fragments[index - 1]
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a_start, a_end = a['match-start'], a['match-end']
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a_len = a_end - a_start
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a_stretch = int(a_len * args.align_stretch_fraction)
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a_shrink = int(a_len * args.align_shrink_fraction)
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a_end = a_end - a_shrink
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a_ext = a_shrink + a_stretch
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else:
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a = None
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a_start = a_end = 0
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if index < len(matched_fragments):
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b = matched_fragments[index]
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b_start, b_end = b['match-start'], b['match-end']
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b_len = b_end - b_start
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b_stretch = int(b_len * args.align_stretch_fraction)
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b_shrink = int(b_len * args.align_shrink_fraction)
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b_start = b_start + b_shrink
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b_ext = b_shrink + b_stretch
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else:
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b = None
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b_start = b_end = len(search.text)
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assert a_end <= b_start
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gap_text = tc.clean_text[a_end:b_start]
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if a_end == b_start or len(gap_text.strip()) == 0:
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assert a_start <= a_end
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assert b_start <= b_end
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if a_end == b_start or a_start == a_end or b_start == b_end:
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continue
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gap_meta = tc.meta[a_end:b_start]
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gap_text = tc.clean_text[a_end - 1:b_start + 1]
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gap_meta = tc.meta[a_end - 1:b_start + 1]
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if a:
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a_best_index, a_similarities = get_similarities(a['transcript'],
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tc.clean_text[a_start:a_end],
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min(len(gap_text) - 1, a_ext),
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gap_text,
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gap_meta,
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1)
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@ -412,6 +423,7 @@ def main(args):
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if b:
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b_best_index, b_similarities = get_similarities(b['transcript'],
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tc.clean_text[b_start:b_end],
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min(len(gap_text) - 1, b_ext),
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gap_text,
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gap_meta,
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-1)
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