The CTC confidences are computed on the encoder while the Transformer is only used for character-wise S2S decoding. We evaluate this setup on three HTR data sets: IAM, Rimes, and StAZH. On IAM, we achieve a competitive Character Error Rate (CER) of 2.95% when pretraining our model on ...
Model c代表输入context,t代表预测target o_c\rightarrow E\rightarrow e_c\rightarrow softmax\rightarrow \hat{y} Softmax: p(t|c) = \frac{\exp(\theta^T_te_c)}{\sum_{j=1}^{10000}{\exp(\theta^T_je_c)}},\space \theta_t:与输出t有关的参数 L(\hat{y},y)=-\sum_{i=1}...
The HGMD regulatory mutation model was trained with L1 regularization parameter 20 and L2 regularization parameter 2,000 for ten iterations. eQTL and GWAS SNP models were trained with L1 regularization parameter 0 and L2 regularization parameter 10 for 100 iterations. 可以看到这两个数据是分开train的,...
前一节讲的attention model就可以用在语音识别里。 另一种效果也不错的方法是用CTC (Connectionist temporal classification)损失函数来做语音识别(Grayes et. al., 2006. Connetionist Temporal Classification: Labeling unsegmented sequence data with recurrent neural networks)。这里使用的神经网络中输入x和输出y的...
this paper propose a small-footprint Keyword Spotting (KWS) system using sequence-to-sequence model based on Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) with Connectionist Temporal Classifier (CTC), and this system which use the Per-channel energy normalization (PCEN) mel feat...
3.8注意力模型(Attention Model) 3.9语音识别(Speech recognition) 3.10触发字检测(Trigger Word Detection) 3.11结论和致谢(Conclusion and thank you) 3.1 基础模型(Basic Models) 在这一周,你将会学习seq2seq(sequence to sequence)模型,从机器翻译到语音识别,它们都能起到很大的作用,从最基本的模型开始。之后你还...
Δdmaxfor someΔdmax. In our model, indels are single nucleotide events occurring with probability *PI. Insertions and deletions are considered equally likely and we treat the distance change as a problem of random walks. Let the random variableWd,PI= the maximum displacement from the origin of...
这与以前的工作中采用的方法是一致的:7-class accuracy7级准确度(即 Acc_7 : Z\cap[-3,3] 中的情感得分分类),binary accuracy二进制精度(即 Acc_2 :正面/负面情绪),F1 score ,mean absolute error (MAE) of the score,和the correlation of the model’s prediction with human(模型预测与人体的相关性...
[0]: model_shapes.max_seq_length=74 ShouldUsePaddedIO [1]: seq_array[i]=74 ShouldUsePaddedIO [1]: model_shapes.max_seq_length=74 ShouldUsePaddedIO rv=false all_max_seq_length=true CudnnRNNBackwardOp use_padded_io=0 GetCachedRnnDescriptor call with use_padded_io=0 --> GetCachedRnn...
syllable based model with the Transformer performs better than CI-phoneme based counterpart, and achieves a character error rate (CER) of \emph{ 28.77\% 28.77\% }, which is competitive to the state-of-the-art CER of 28.0\% 28.0\% by the joint CTC-attention based encoder-decoder network....