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Add model files

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README.md ADDED
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+ Dataset: Common Voice zh-HK
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+ CER: 17.810267
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+
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+ evaluation code
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+
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+ ```python3
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+ import torch
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+ import torchaudio
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+ from datasets import load_dataset, load_metric
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+ from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
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+ import re
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+ import argparse
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+
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+ lang_id = "zh-HK"
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+ model_id = "./wav2vec2-large-xlsr-cantonese"
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+
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+ parser = argparse.ArgumentParser(description='hanles checkpoint loading')
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+ parser.add_argument('--checkpoint', type=str, default=None)
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+ args = parser.parse_args()
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+ model_path = model_id
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+ if args.checkpoint is not None:
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+ model_path += "/checkpoint-" + args.checkpoint
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+
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+
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+ chars_to_ignore_regex = '[\,\?\.\!\-\;\:"\“\%\‘\”\�\.\⋯\!\-\:\–\。\》\,\)\,\?\;\~\~\…\︰\,\(\」\‧\《\﹔\、\—\/\,\「\﹖\·\']'
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+
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+ test_dataset = load_dataset("common_voice", f"{lang_id}", split="test")
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+ cer = load_metric("./cer")
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+
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+ processor = Wav2Vec2Processor.from_pretrained(f"{model_id}")
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+ model = Wav2Vec2ForCTC.from_pretrained(f"{model_path}")
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+ model.to("cuda")
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+
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+ resampler = torchaudio.transforms.Resample(48_000, 16_000)
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+
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+ # Preprocessing the datasets.
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+ # We need to read the aduio files as arrays
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+ def speech_file_to_array_fn(batch):
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+ batch["sentence"] = re.sub(chars_to_ignore_regex, '', batch["sentence"]).lower()
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+ speech_array, sampling_rate = torchaudio.load(batch["path"])
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+ batch["speech"] = resampler(speech_array).squeeze().numpy()
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+ return batch
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+
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+ test_dataset = test_dataset.map(speech_file_to_array_fn)
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+
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+ # Preprocessing the datasets.
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+ # We need to read the aduio files as arrays
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+ def evaluate(batch):
49
+ inputs = processor(batch["speech"], sampling_rate=16_000, return_tensors="pt", padding=True)
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+ with torch.no_grad():
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+ logits = model(inputs.input_values.to("cuda"), attention_mask=inputs.attention_mask.to("cuda")).logits
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+
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+ pred_ids = torch.argmax(logits, dim=-1)
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+ batch["pred_strings"] = processor.batch_decode(pred_ids)
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+ return batch
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+
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+ result = test_dataset.map(evaluate, batched=True, batch_size=16)
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+
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+ print("CER: {:2f}".format(100 * cer.compute(predictions=result["pred_strings"], references=result["sentence"])))
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+ ```
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+
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+ Character Error Rate implementation
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+
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+ ```python3
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+ @datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION, _KWARGS_DESCRIPTION)
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+ class CER(datasets.Metric):
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+ def _info(self):
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+ return datasets.MetricInfo(
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+ description=_DESCRIPTION,
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+ citation=_CITATION,
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+ inputs_description=_KWARGS_DESCRIPTION,
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+ features=datasets.Features(
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+ {
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+ "predictions": datasets.Value("string", id="sequence"),
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+ "references": datasets.Value("string", id="sequence"),
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+ }
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+ ),
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+ codebase_urls=["https://github.com/jitsi/jiwer/"],
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+ reference_urls=[
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+ "https://en.wikipedia.org/wiki/Word_error_rate",
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+ ],
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+ )
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+
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+ def _compute(self, predictions, references):
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+ preds = [char for seq in predictions for char in list(seq)]
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+ refs = [char for seq in references for char in list(seq)]
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+ return wer(refs, preds)
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+ ```
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+
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+ will post the training code later.
cer.py ADDED
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+ # coding=utf-8
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+ # Copyright 2021 The HuggingFace Datasets Authors.
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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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+ """ Word Error Ratio (WER) metric. """
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+
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+ from jiwer import wer
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+
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+ import datasets
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+
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+
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+ _CITATION = """\
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+ @inproceedings{inproceedings,
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+ author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
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+ year = {2004},
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+ month = {01},
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+ pages = {},
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+ title = {From WER and RIL to MER and WIL: improved evaluation measures for connected speech recognition.}
29
+ }
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+ """
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+
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+ _DESCRIPTION = """\
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+ Word error rate (WER) is a common metric of the performance of an automatic speech recognition system.
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+
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+ The general difficulty of measuring performance lies in the fact that the recognized word sequence can have a different length from the reference word sequence (supposedly the correct one). The WER is derived from the Levenshtein distance, working at the word level instead of the phoneme level. The WER is a valuable tool for comparing different systems as well as for evaluating improvements within one system. This kind of measurement, however, provides no details on the nature of translation errors and further work is therefore required to identify the main source(s) of error and to focus any research effort.
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+
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+ This problem is solved by first aligning the recognized word sequence with the reference (spoken) word sequence using dynamic string alignment. Examination of this issue is seen through a theory called the power law that states the correlation between perplexity and word error rate.
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+
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+ Word error rate can then be computed as:
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+
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+ WER = (S + D + I) / N = (S + D + I) / (S + D + C)
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+
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+ where
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+
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+ S is the number of substitutions,
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+ D is the number of deletions,
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+ I is the number of insertions,
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+ C is the number of correct words,
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+ N is the number of words in the reference (N=S+D+C).
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+
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+ WER's output is always a number between 0 and 1. This value indicates the percentage of words that were incorrectly predicted. The lower the value, the better the
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+ performance of the ASR system with a WER of 0 being a perfect score.
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+ """
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+
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+ _KWARGS_DESCRIPTION = """
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+ Computes WER score of transcribed segments against references.
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+ Args:
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+ references: list of references for each speech input.
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+ predictions: list of transcribtions to score.
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+ Returns:
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+ (float): the word error rate
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+
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+ Examples:
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+
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+ >>> predictions = ["this is the prediction", "there is an other sample"]
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+ >>> references = ["this is the reference", "there is another one"]
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+ >>> wer = datasets.load_metric("wer")
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+ >>> wer_score = wer.compute(predictions=predictions, references=references)
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+ >>> print(wer_score)
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+ 0.5
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+ """
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+
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+
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+ @datasets.utils.file_utils.add_start_docstrings(_DESCRIPTION, _KWARGS_DESCRIPTION)
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+ class CER(datasets.Metric):
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+ def _info(self):
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+ return datasets.MetricInfo(
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+ description=_DESCRIPTION,
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+ citation=_CITATION,
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+ inputs_description=_KWARGS_DESCRIPTION,
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+ features=datasets.Features(
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+ {
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+ "predictions": datasets.Value("string", id="sequence"),
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+ "references": datasets.Value("string", id="sequence"),
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+ }
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+ ),
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+ codebase_urls=["https://github.com/jitsi/jiwer/"],
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+ reference_urls=[
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+ "https://en.wikipedia.org/wiki/Word_error_rate",
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+ ],
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+ )
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+
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+ def _compute(self, predictions, references):
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+ preds = [char for seq in predictions for char in list(seq)]
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+ refs = [char for seq in references for char in list(seq)]
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+ return wer(refs, preds)
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+ """
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+ wers = []
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+ for pred, ref in zip(predictions, references):
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+ wers.append(wer(list(ref), list(pred)))
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+ return sum(wers) / len(wers)
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+ """
config.json ADDED
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"潤": 1464, "敢": 1465, "貴": 1466, "挽": 1467, "嗇": 1468, "巾": 1469, "役": 1470, "汝": 1471, "龢": 1472, "引": 1473, "斷": 1474, "茨": 1475, "噶": 1476, "叔": 1477, "加": 1478, "台": 1479, "性": 1480, "璽": 1481, "藉": 1482, "風": 1483, "桃": 1484, "鳩": 1485, "芹": 1486, "娥": 1487, "又": 1488, "猶": 1489, "毓": 1490, "影": 1491, "靖": 1492, "冷": 1493, "傅": 1494, "版": 1495, "顯": 1496, "鼻": 1497, "百": 1498, "恆": 1499, "秒": 1500, "莞": 1501, "寒": 1502, "璇": 1503, "煞": 1504, "匿": 1505, "妓": 1506, "石": 1507, "枱": 1508, "折": 1509, "淥": 1510, "程": 1511, "顏": 1512, "劇": 1513, "暇": 1514, "藐": 1515, "釘": 1516, "易": 1517, "外": 1518, "篳": 1519, "熾": 1520, "旳": 1521, "小": 1522, "僑": 1523, "菓": 1524, "舍": 1525, "怯": 1526, "砸": 1527, "救": 1528, "媒": 1529, "徇": 1530, "踹": 1531, "飼": 1532, "道": 1533, "週": 1534, "萃": 1535, "亨": 1536, "囍": 1537, "厭": 1538, "蹟": 1539, "翻": 1540, "苦": 1541, "量": 1542, "嗡": 1543, "挨": 1544, "苟": 1545, "鼠": 1546, "賓": 1547, "認": 1548, "忿": 1549, "呱": 1550, "攬": 1551, "琴": 1552, "稍": 1553, "兔": 1554, "幫": 1555, "款": 1556, "嘥": 1557, "攀": 1558, "廳": 1559, "蓋": 1560, "噹": 1561, "轡": 1562, "展": 1563, "蘸": 1564, "雙": 1565, "孕": 1566, "霖": 1567, "腎": 1568, "魅": 1569, "豂": 1570, "噁": 1571, "惑": 1572, "職": 1573, "㗎": 1574, "硤": 1575, "屑": 1576, "戥": 1577, "橙": 1578, "迴": 1579, "瀝": 1580, "粼": 1581, "渝": 1582, "墜": 1583, "孭": 1584, "紮": 1585, "線": 1586, "形": 1587, "錶": 1588, "核": 1589, "獻": 1590, "雷": 1591, "岀": 1592, "霜": 1593, "璈": 1594, "復": 1595, "股": 1596, "怕": 1597, "乳": 1598, "簽": 1599, "難": 1600, "遂": 1601, "既": 1602, "釗": 1603, "呷": 1604, "蝦": 1605, "穿": 1606, "掘": 1607, "晝": 1608, "地": 1609, "憩": 1610, "嚴": 1611, "丰": 1612, "妙": 1613, "蝕": 1614, "佑": 1615, "詹": 1616, "袁": 1617, "羹": 1618, "妄": 1619, "鬥": 1620, "某": 1621, "茶": 1622, "黐": 1623, "對": 1624, "嚿": 1625, "作": 1626, "殺": 1627, "菠": 1628, "堪": 1629, "潑": 1630, "丹": 1631, "缸": 1632, "辭": 1633, "簡": 1634, "尾": 1635, "嘩": 1636, "雞": 1637, "h": 1638, "她": 1639, "欽": 1640, "針": 1641, "技": 1642, "軟": 1643, "持": 1644, "俎": 1645, "印": 1646, "忌": 1647, "糕": 1648, "現": 1649, "嚼": 1650, "腳": 1651, "備": 1652, "殼": 1653, "坤": 1654, "嚡": 1655, "組": 1656, "膠": 1657, "損": 1658, "休": 1659, "不": 1660, "樓": 1661, "黑": 1662, "弄": 1663, "肚": 1664, "丁": 1665, "撓": 1666, "吊": 1667, "柑": 1668, "盛": 1669, "啩": 1670, "璧": 1671, "滂": 1672, "蘇": 1673, "寧": 1674, "官": 1675, "嘈": 1676, "准": 1677, "窿": 1678, "計": 1679, "掃": 1680, "塵": 1681, "孔": 1682, "落": 1683, "撒": 1684, "擲": 1685, "貢": 1686, "附": 1687, "獲": 1688, "椒": 1689, "鄂": 1690, "墳": 1691, "業": 1692, "識": 1693, "奇": 1694, "迫": 1695, "偶": 1696, "扯": 1697, "唪": 1698, "卡": 1699, "崇": 1700, "栽": 1701, "誘": 1702, "甩": 1703, "厥": 1704, "予": 1705, "醉": 1706, "吠": 1707, "錢": 1708, "庶": 1709, "姓": 1710, "索": 1711, "濫": 1712, "譎": 1713, "呂": 1714, "醬": 1715, "傾": 1716, "娛": 1717, "棗": 1718, "蠻": 1719, "構": 1720, "牡": 1721, "力": 1722, "娜": 1723, "唸": 1724, "牛": 1725, "憚": 1726, "慰": 1727, "燉": 1728, "憶": 1729, "京": 1730, "牲": 1731, "瞌": 1732, "唈": 1733, "植": 1734, "膺": 1735, "癆": 1736, "蓆": 1737, "鸞": 1738, "斬": 1739, "臺": 1740, "車": 1741, "偈": 1742, "鴨": 1743, "豉": 1744, "晏": 1745, "爺": 1746, "墟": 1747, "聳": 1748, "搽": 1749, "隊": 1750, "縛": 1751, "蠅": 1752, "級": 1753, "波": 1754, "合": 1755, "恩": 1756, "裙": 1757, "踐": 1758, "塘": 1759, "咩": 1760, "萄": 1761, "鉸": 1762, "耍": 1763, "斯": 1764, "坦": 1765, "誰": 1766, "粿": 1767, "搣": 1768, "派": 1769, "但": 1770, "跑": 1771, "捷": 1772, "抖": 1773, "咇": 1774, "渺": 1775, "閱": 1776, "餒": 1777, "爆": 1778, "疵": 1779, "掕": 1780, "拘": 1781, "寫": 1782, "疊": 1783, "赤": 1784, "蒙": 1785, "越": 1786, "角": 1787, "睡": 1788, "棚": 1789, "芒": 1790, "儈": 1791, "亢": 1792, "旬": 1793, "鐵": 1794, "弟": 1795, "尬": 1796, "壆": 1797, "瘓": 1798, "孝": 1799, "錦": 1800, "潺": 1801, "念": 1802, "盧": 1803, "蕃": 1804, "極": 1805, "伯": 1806, "撐": 1807, "謁": 1808, "期": 1809, "蓉": 1810, "機": 1811, "欠": 1812, "拙": 1813, "滅": 1814, "嗤": 1815, "岬": 1816, "垃": 1817, "穗": 1818, "蕩": 1819, "璃": 1820, "傢": 1821, "抿": 1822, "鵝": 1823, "晃": 1824, "喃": 1825, "謹": 1826, "再": 1827, "艷": 1828, "察": 1829, "兮": 1830, "戰": 1831, "俚": 1832, "優": 1833, "瓊": 1834, "黃": 1835, "鳴": 1836, "所": 1837, "昏": 1838, "直": 1839, "館": 1840, "d": 1841, "爾": 1842, "據": 1843, "芳": 1844, "氧": 1845, "荒": 1846, "叮": 1847, "右": 1848, "掟": 1849, "敲": 1850, "仙": 1851, "魁": 1852, "蟲": 1853, "彩": 1854, "緘": 1855, "篋": 1856, "凡": 1857, "準": 1858, "讎": 1859, "瑧": 1860, "圭": 1861, "邏": 1862, "囊": 1863, "拓": 1864, "温": 1865, "邨": 1866, "笠": 1867, "槽": 1868, "掅": 1869, "董": 1870, "旁": 1871, "雲": 1872, "語": 1873, "柔": 1874, "鍵": 1875, "卑": 1876, "摯": 1877, "崆": 1878, "孱": 1879, "裕": 1880, "j": 1881, "群": 1882, "選": 1883, "鳶": 1884, "暑": 1885, "順": 1886, "胡": 1887, "珏": 1888, "紅": 1889, "呀": 1890, "後": 1891, "包": 1892, "富": 1893, "兒": 1894, "迾": 1895, "義": 1896, "畀": 1897, "菊": 1898, "餸": 1899, "伸": 1900, "悖": 1901, "薈": 1902, "濕": 1903, "攞": 1904, "櫈": 1905, "證": 1906, "申": 1907, "江": 1908, "皂": 1909, "紛": 1910, "癢": 1911, "秅": 1912, "戶": 1913, "希": 1914, "熟": 1915, "祭": 1916, "咸": 1917, "咬": 1918, "鮭": 1919, "堡": 1920, "遠": 1921, "乎": 1922, "近": 1923, "漲": 1924, "乾": 1925, "宗": 1926, "坊": 1927, "趾": 1928, "奈": 1929, "遺": 1930, "鈴": 1931, "纔": 1932, "茵": 1933, "抱": 1934, "堅": 1935, "佗": 1936, "醒": 1937, "載": 1938, "帥": 1939, "蝨": 1940, "少": 1941, "鱔": 1942, "狠": 1943, "澩": 1944, "暸": 1945, "蔬": 1946, "巷": 1947, "抽": 1948, "契": 1949, "薇": 1950, "犀": 1951, "東": 1952, "佻": 1953, "紓": 1954, "旗": 1955, "網": 1956, "睇": 1957, "咿": 1958, "曲": 1959, "x": 1960, "鬼": 1961, "勝": 1962, "幅": 1963, "意": 1964, "行": 1965, "貂": 1966, "亂": 1967, "磨": 1968, "宇": 1969, "十": 1970, "馨": 1971, "沾": 1972, "蛟": 1973, "遊": 1974, "酥": 1975, "頻": 1976, "翌": 1977, "好": 1978, "輕": 1979, "盪": 1980, "畫": 1981, "靜": 1982, "唐": 1983, "跳": 1984, "葡": 1985, "邈": 1986, "峯": 1987, "領": 1988, "杭": 1989, "舨": 1990, "下": 1991, "潘": 1992, "汪": 1993, "尺": 1994, "題": 1995, "騭": 1996, "吝": 1997, "嫉": 1998, "隸": 1999, "碧": 2000, "滘": 2001, "褲": 2002, "暫": 2003, "衝": 2004, "喫": 2005, "墓": 2006, "賊": 2007, "別": 2008, "捱": 2009, "家": 2010, "摞": 2011, "内": 2012, "壯": 2013, "招": 2014, "入": 2015, "覆": 2016, "粳": 2017, "哭": 2018, "埗": 2019, "逢": 2020, "勳": 2021, "文": 2022, "揦": 2023, "製": 2024, "限": 2025, "整": 2026, "嗜": 2027, "彥": 2028, "征": 2029, "像": 2030, "鰂": 2031, "膊": 2032, "籬": 2033, "旱": 2034, "瑟": 2035, "高": 2036, "荊": 2037, "宅": 2038, "夥": 2039, "賬": 2040, "臻": 2041, "戊": 2042, "頗": 2043, "骨": 2044, "庫": 2045, "蔥": 2046, "差": 2047, "鋁": 2048, "幸": 2049, "謝": 2050, "拮": 2051, "糾": 2052, "克": 2053, "冇": 2054, "本": 2055, "倫": 2056, "蘭": 2057, "峽": 2058, "懇": 2059, "燜": 2060, "截": 2061, "磯": 2062, "立": 2063, "歇": 2064, "愉": 2065, "賭": 2066, "講": 2067, "咦": 2068, "哼": 2069, "孖": 2070, "概": 2071, "銀": 2072, "朝": 2073, "憑": 2074, "然": 2075, "竅": 2076, "妻": 2077, "分": 2078, "始": 2079, "熙": 2080, "嘟": 2081, "旭": 2082, "輻": 2083, "餃": 2084, "爸": 2085, "搏": 2086, "址": 2087, "繞": 2088, "被": 2089, "芭": 2090, "累": 2091, "際": 2092, "玻": 2093, "精": 2094, "吾": 2095, "逸": 2096, "禡": 2097, "遇": 2098, "陂": 2099, "並": 2100, "用": 2101, "琳": 2102, "擎": 2103, "啲": 2104, "癲": 2105, "掠": 2106, "較": 2107, "湯": 2108, "離": 2109, "舌": 2110, "縷": 2111, "眨": 2112, "戚": 2113, "召": 2114, "擋": 2115, "鹹": 2116, "給": 2117, "歹": 2118, "埋": 2119, "南": 2120, "凶": 2121, "雅": 2122, "澄": 2123, "亮": 2124, "短": 2125, "演": 2126, "障": 2127, "流": 2128, "漆": 2129, "喚": 2130, "屹": 2131, "駿": 2132, "且": 2133, "執": 2134, "啫": 2135, "劖": 2136, "溫": 2137, "慷": 2138, "芙": 2139, "毡": 2140, "莓": 2141, "楊": 2142, "種": 2143, "烘": 2144, "肴": 2145, "譜": 2146, "䰧": 2147, "典": 2148, "破": 2149, "褒": 2150, "豪": 2151, "抓": 2152, "模": 2153, "蛛": 2154, "壟": 2155, "州": 2156, "擸": 2157, "湃": 2158, "毛": 2159, "腦": 2160, "開": 2161, "烟": 2162, "柱": 2163, "路": 2164, "喜": 2165, "拳": 2166, "衷": 2167, "咪": 2168, "似": 2169, "號": 2170, "峒": 2171, "闆": 2172, "苗": 2173, "厴": 2174, "逐": 2175, "戾": 2176, "胃": 2177, "涕": 2178, "昭": 2179, "咽": 2180, "戀": 2181, "質": 2182, "肋": 2183, "傲": 2184, "梗": 2185, "丟": 2186, "校": 2187, "肖": 2188, "嗦": 2189, "訓": 2190, "姬": 2191, "睛": 2192, "肇": 2193, "次": 2194, "浣": 2195, "嶄": 2196, "瀨": 2197, "哉": 2198, "居": 2199, "巨": 2200, "恤": 2201, "漂": 2202, "寡": 2203, "可": 2204, "寇": 2205, "使": 2206, "鱸": 2207, "嚐": 2208, "割": 2209, "殷": 2210, "笏": 2211, "己": 2212, "惘": 2213, "蹋": 2214, "阪": 2215, "宜": 2216, "嘢": 2217, "撞": 2218, "鰻": 2219, "三": 2220, "甜": 2221, "廂": 2222, "浚": 2223, "我": 2224, "姊": 2225, "什": 2226, "購": 2227, "梅": 2228, "詭": 2229, "飢": 2230, "維": 2231, "窄": 2232, "黜": 2233, "枉": 2234, "惡": 2235, "稱": 2236, "澡": 2237, "梨": 2238, "両": 2239, "孫": 2240, "估": 2241, "圍": 2242, "盤": 2243, "默": 2244, "束": 2245, "科": 2246, "鴉": 2247, "氹": 2248, "鞦": 2249, "簾": 2250, "鬱": 2251, "晒": 2252, "蹤": 2253, "病": 2254, "梁": 2255, "進": 2256, "悉": 2257, "交": 2258, "硬": 2259, "霸": 2260, "迎": 2261, "舅": 2262, "湘": 2263, "輩": 2264, "侯": 2265, "邰": 2266, "匹": 2267, "板": 2268, "揗": 2269, "莉": 2270, "恙": 2271, "蒲": 2272, "推": 2273, "豁": 2274, "坑": 2275, "決": 2276, "唥": 2277, "庵": 2278, "過": 2279, "無": 2280, "衫": 2281, "禍": 2282, "詩": 2283, "竹": 2284, "叫": 2285, "輊": 2286, "勞": 2287, "䒏": 2288, "險": 2289, "列": 2290, "畿": 2291, "吓": 2292, "劃": 2293, "轉": 2294, "途": 2295, "謢": 2296, "奔": 2297, "制": 2298, "闊": 2299, "瑞": 2300, "珒": 2301, "佩": 2302, "煙": 2303, "願": 2304, "欣": 2305, "上": 2306, "恃": 2307, "徊": 2308, "閘": 2309, "誇": 2310, "籮": 2311, "q": 2312, "襪": 2313, "根": 2314, "涯": 2315, "佔": 2316, "秦": 2317, "霧": 2318, "瓏": 2319, "喪": 2320, "躁": 2321, "佳": 2322, "啊": 2323, "彈": 2324, "斂": 2325, "萍": 2326, "受": 2327, "殮": 2328, "襯": 2329, "鉤": 2330, "嬉": 2331, "五": 2332, "速": 2333, "酒": 2334, "算": 2335, "甘": 2336, "揮": 2337, "侍": 2338, "妥": 2339, "蠱": 2340, "數": 2341, "臉": 2342, "方": 2343, "導": 2344, "彤": 2345, "點": 2346, "判": 2347, "留": 2348, "裔": 2349, "祠": 2350, "狀": 2351, "熬": 2352, "跌": 2353, "迦": 2354, "省": 2355, "頭": 2356, "類": 2357, "岡": 2358, "佐": 2359, "剷": 2360, "巫": 2361, "心": 2362, "恢": 2363, "育": 2364, "藝": 2365, "麝": 2366, "老": 2367, "腐": 2368, "炆": 2369, "杉": 2370, "何": 2371, "扭": 2372, "煎": 2373, "槍": 2374, "碉": 2375, "財": 2376, "炮": 2377, "胎": 2378, "楓": 2379, "獨": 2380, "助": 2381, "采": 2382, "穌": 2383, "挖": 2384, "荔": 2385, "票": 2386, "剝": 2387, "枚": 2388, "驕": 2389, "梭": 2390, "贼": 2391, "冰": 2392, "趺": 2393, "距": 2394, "書": 2395, "沽": 2396, "壩": 2397, "牙": 2398, "糯": 2399, "妨": 2400, "砌": 2401, "棲": 2402, "檢": 2403, "卸": 2404, "保": 2405, "允": 2406, "中": 2407, "格": 2408, "矮": 2409, "鑑": 2410, "瞞": 2411, "哥": 2412, "慘": 2413, "榨": 2414, "肛": 2415, "你": 2416, "豐": 2417, "睄": 2418, "雄": 2419, "鳥": 2420, "紀": 2421, "鼆": 2422, "迅": 2423, "說": 2424, "碘": 2425, "姑": 2426, "侶": 2427, "立": 2428, "要": 2429, "遮": 2430, "蹄": 2431, "養": 2432, "摷": 2433, "堆": 2434, "徽": 2435, "趴": 2436, "側": 2437, "術": 2438, "澳": 2439, "敏": 2440, "月": 2441, "銷": 2442, "抗": 2443, "絶": 2444, "司": 2445, "乃": 2446, "羈": 2447, "g": 2448, "素": 2449, "罷": 2450, "瀚": 2451, "翼": 2452, "譯": 2453, "卓": 2454, "魂": 2455, "綁": 2456, "顱": 2457, "才": 2458, "細": 2459, "弱": 2460, "瞅": 2461, "撤": 2462, "摸": 2463, "慶": 2464, "捩": 2465, "仿": 2467, "患": 2468, "拼": 2469, "菜": 2470, "芽": 2471, "變": 2472, "教": 2473, "凝": 2474, "昧": 2475, "鈔": 2476, "火": 2477, "俗": 2478, "淸": 2479, "丸": 2480, "笪": 2481, "灘": 2482, "姻": 2483, "踩": 2484, "照": 2485, "織": 2486, "攏": 2487, "棘": 2488, "賃": 2489, "蝴": 2490, "材": 2491, "噃": 2492, "迂": 2493, "r": 2494, "穎": 2495, "滾": 2496, "羣": 2497, "憂": 2498, "泡": 2499, "聖": 2500, "揭": 2501, "螺": 2502, "濟": 2503, "屬": 2504, "垂": 2505, "挺": 2506, "囚": 2507, "檻": 2508, "㩿": 2509, "篙": 2510, "肘": 2511, "胸": 2512, "泰": 2513, "籤": 2514, "河": 2515, "規": 2516, "娃": 2517, "斐": 2518, "撕": 2519, "拯": 2520, "倉": 2521, "伐": 2522, "訂": 2523, "鏡": 2524, "獎": 2525, "慣": 2526, "姦": 2527, "膨": 2528, "篇": 2529, "停": 2530, "魄": 2531, "腰": 2532, "杖": 2533, "謬": 2534, "匙": 2535, "一": 2536, "售": 2537, "渦": 2538, "海": 2539, "惱": 2540, "砵": 2541, "薯": 2542, "案": 2543, "唯": 2544, "鬠": 2545, "孟": 2546, "樣": 2547, "逝": 2548, "米": 2549, "基": 2550, "乘": 2551, "扶": 2552, "徹": 2553, "嶙": 2554, "友": 2555, "櫃": 2556, "水": 2557, "儲": 2558, "倦": 2559, "懿": 2560, "俏": 2561, "鴦": 2562, "k": 2563, "瘋": 2564, "尊": 2565, "厄": 2566, "裝": 2567, "羲": 2568, "瑰": 2569, "院": 2570, "懶": 2571, "攔": 2572, "名": 2573, "脫": 2574, "攣": 2575, "陰": 2576, "粉": 2577, "局": 2578, "輝": 2579, "晾": 2580, "来": 2581, "鑊": 2582, "攘": 2583, "釜": 2584, "觀": 2585, "棉": 2586, "鱲": 2587, "懣": 2588, "辣": 2589, "焚": 2590, "豹": 2591, "袋": 2592, "禁": 2593, "殖": 2594, "兆": 2595, "捶": 2596, "暮": 2597, "甴": 2598, "額": 2599, "席": 2600, "吩": 2601, "暗": 2602, "賺": 2603, "漓": 2604, "滄": 2605, "安": 2606, "卵": 2607, "氏": 2608, "括": 2609, "貿": 2610, "活": 2611, "鎖": 2612, "習": 2613, "紗": 2614, "塑": 2615, "蹈": 2616, "鴻": 2617, "沈": 2618, "狼": 2619, "擬": 2620, "俸": 2621, "陽": 2622, "貧": 2623, "啵": 2624, "煲": 2625, "肌": 2626, "⠀": 2627, "渡": 2628, "樑": 2629, "悗": 2630, "禮": 2631, "盡": 2632, "須": 2633, "供": 2634, "齷": 2635, "濃": 2636, "屙": 2637, "人": 2638, "幢": 2639, "捋": 2640, "軒": 2641, "松": 2642, "哨": 2643, "笈": 2644, "完": 2645, "餵": 2646, "寞": 2647, "昇": 2648, "奮": 2649, "墅": 2650, "寢": 2651, "恒": 2652, "尿": 2653, "暉": 2654, "烏": 2655, "姆": 2656, "馳": 2657, "喝": 2658, "砰": 2659, "果": 2660, "梧": 2661, "首": 2662, "討": 2663, "虎": 2664, "元": 2665, "怖": 2666, "毀": 2667, "懼": 2668, "剎": 2669, "揪": 2670, "磡": 2671, "滯": 2672, "僕": 2673, "雍": 2674, "喊": 2675, "郁": 2676, "姿": 2677, "雀": 2678, "片": 2679, "取": 2680, "吧": 2681, "柏": 2682, "盾": 2683, "狄": 2684, "驚": 2685, "論": 2686, "潮": 2687, "廿": 2688, "赴": 2689, "塊": 2690, "喂": 2691, "娘": 2692, "駛": 2693, "朵": 2694, "料": 2695, "景": 2696, "巢": 2697, "稻": 2698, "況": 2699, "囌": 2700, "港": 2701, "勃": 2702, "抄": 2703, "咐": 2704, "瑪": 2705, "沙": 2706, "貓": 2707, "另": 2708, "僱": 2709, "眠": 2710, "更": 2711, "扻": 2712, "香": 2713, "鱷": 2714, "洛": 2715, "啱": 2716, "建": 2717, "呻": 2718, "筲": 2719, "洱": 2720, "鍚": 2721, "韓": 2722, "藏": 2723, "甫": 2724, "鈕": 2725, "常": 2726, "剪": 2727, "漬": 2728, "併": 2729, "串": 2730, "聘": 2731, "陷": 2732, "謙": 2733, "肯": 2734, "汗": 2735, "敷": 2736, "訪": 2737, "敬": 2738, "史": 2739, "否": 2740, "息": 2741, "宰": 2742, "憎": 2743, "及": 2744, "吶": 2745, "熔": 2746, "卧": 2747, "慾": 2748, "蔔": 2749, "謀": 2750, "皇": 2751, "爽": 2752, "圳": 2753, "略": 2754, "糍": 2755, "揉": 2756, "舞": 2757, "纜": 2758, "迪": 2759, "狂": 2760, "巴": 2761, "料": 2762, "價": 2763, "斤": 2764, "釀": 2765, "筒": 2766, "蜆": 2767, "檀": 2768, "帝": 2769, "新": 2770, "魚": 2771, "豎": 2772, "飯": 2773, "冠": 2774, "髮": 2775, "畐": 2776, "瓶": 2777, "封": 2778, "廬": 2779, "谷": 2780, "賣": 2781, "弓": 2782, "頂": 2783, "隅": 2784, "閣": 2785, "市": 2786, "柵": 2787, "氯": 2788, "玄": 2789, "洶": 2790, "溢": 2791, "咕": 2792, "皚": 2793, "兌": 2794, "厲": 2795, "喐": 2796, "p": 2797, "漁": 2798, "舟": 2799, "臨": 2800, "柯": 2801, "而": 2802, "洪": 2803, "棍": 2804, "寬": 2805, "牯": 2806, "衲": 2807, "誠": 2808, "窒": 2809, "麥": 2810, "插": 2811, "雪": 2812, "店": 2813, "狗": 2814, "副": 2815, "挈": 2816, "晶": 2817, "失": 2818, "狡": 2819, "妳": 2820, "裏": 2821, "烈": 2822, "煤": 2823, "的": 2824, "漫": 2825, "濛": 2826, "捺": 2827, "椅": 2828, "平": 2829, 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