log(c) return llForward ctc_beam_search 解码 def ctc_beam_search_decode(probs, beam_size=5, blank=0): """ :param probs: The output probabilities (e.g. post-softmax) for each time step. Should be an array of shape (time x output dim). :param beam: :param blank: :return: ...
l∗=argmaxp(l|x) 假设有字符列表(′−′,′A′,′B′),时刻T=3,并且定义在t时刻时,字符c出现的概率为P(c,t)。如下表所示,以横轴作为时刻序列,纵轴为字符列表,表格中的数字为概率,我们的目标是在这个二维空间中搜索出概率最大的标签l∗。 greedy decode 贪心的思想是每次都要最好的,那也就是说...
ctc decode的输入输出都是list,中间过程使用tensor就行。 代码如下 classCtc_Decode:# 用tf定义一个专门ctc解码的图和会话,就不会一直增加节点了,速度快了很多def__init__(self,batch_size,timestep,nclass):self.batch_size=batch_sizeself.timestep=timestepself.nclass=nclassself.graph_ctc=tf.Graph()with...
fromctcdecodeimportCTCBeamDecoder decoder = CTCBeamDecoder( labels, model_path=None, alpha=0, beta=0, cutoff_top_n=40, cutoff_prob=1.0, beam_width=100, num_processes=4, blank_id=0, log_probs_input=False) beam_results, beam_scores, timesteps, out_lens = decoder.decode(output) ...
gradle的自动构建是非常好用的。有一些人即使不开发软件电脑里也会安装这样的使用功能以防备用，但是，...
# 编写简易版解码器 def ctc_decode(text, blank=10): """ 简易CTC解码器 :param text: 待解码数据 :param blank: 分隔符索引值 :return: 解码后数据 """ result = [] cache_idx = -1 for char in text: if char != blank and char != cache_idx: result.append(char) cache_idx = char ret...
frompyctcdecodeimportbuild_ctcdecoder# specify alphabet labels as they appear in logitslabels=[" ","a","b","c","d","e","f","g","h","i","j","k","l","m","n","o","p","q","r","s","t","u","v","w","x","y","z", ]# prepare decoder and decode logits via...
(c) 2019 Oxford Nanopore Technologies Ltd. fast-ctc-decode is distributed under the terms of the MIT License. If a copy of the License was not distributed with this file, You can obtain one athttps://github.com/nanoporetech/fast-ctc-decode/ ...
ctc_out = K.get_value(ctc_decode)[:, :cfg.label_len] result_str =''.join([cfg.characters[c]forcinctc_out[0]]) result_str = result_str.replace('-','')returnresult_str 开发者ID:kurapan,项目名称:CRNN,代码行数:10,代码来源:eval.py ...
CTC的Decode算法-Prefix Beam Search↩ 连接时序分类↩ Sequence Transduction with Recurrent Neural Networks↩ Streaming End-to-end Speech Recognition for Mobile Devices↩ An overview of end-to-end automatic speech recognition↩↩ On Using Monolingual Corpora in Neural Machine Translation↩ ...