[笔记]Attention-Based Models for Speech Recognition 这篇文章是Bengio的,用attention模型做语音识别。语音识别应该算是和文字识别最相似的一个领域了,输入输出都是一个序列。机器翻译任务的输入输出也都是一个序列,但是机器翻译每一步的输… 旷野里的风打开...
这篇文章是Bengio的,用attention模型做语音识别。语音识别应该算是和文字识别最相似的一个领域了,输入输出都是一个序列。机器翻译任务的输入输出也都是一个序列,但是机器翻译每一步的输出所依赖的信息可能来自输入任何位置,而语音识别和文字识别每一步输出所依赖的信息是输入的一个局部连续序列。但是语音识别与文字识别...
看这个论文的时候我主要是从第三小节开始看起的,也就是 attention-based models 我们基于attention机制的模型大致上可以分为广泛的两类:一类就是全局attention,一类就是局部attention。这两类的区分点在于attention是基于原始句子的全部位置,还是原始句子中一部分位置。 在这篇论文中的attention,获得解码器在t时刻真正的...
一.智能对话中的意图识别和槽填充联合建模,类似于知识图谱中的关系提取和实体识别。一种方法是利用两种模型分别建模;另一种是将两种模型整合到一起做联合建模型。意图识别基本上是文本分类,而槽填充基本上是序列标注。本方法是基于文章《Attention-Based Recurrent Neural Network Models for Joint Intent Detection and ...
Attention-based models have recently shown great performance on a range of tasks, such as speech recognition, machine translation, and image captioning due to their ability to summarize relevant information that expands through the entire length of an input sequence. In this paper, we analyze the ...
Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling(翻译) 基于注意的递归神经网络模型用于联合意图检测和槽填充 摘要 提出基于注意力的神经网络模型用于构建意图识别和槽填充的联合模型 1. 简介 意图识别:意图识别可以看做语义表达的分类问题,流行的方法如支持向量机和深度神经...
论文《Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling》简称Attention BiRNN,作者Bing Liu(Electrical and Computer Engineering, Carnegie Mellon University)。经典的NLU论文(Semantic Frame)。 2. 摘要 基于注意力的编解码器神经网络模型最近在机器翻译和语音识别中显示出令...
12 Commits .idea configs data down-stream-tasks loss model optim resources trainer util .DS_Store README.md run.py README EMO OfficialPyTorchimplementation of "Rethinking Mobile Block for Efficient Attention-based Models, ICCV'23". Abstract:This paper focuses on developing modern, efficient, light...
Most current theoretical models of dreaming are built around air assumption that dream reports collected oil awakening provide unbiased sampling of previous cognitive activity during sleep. However, such data arc retrospective, requiring the recall of previous mental events from sleep on awakening. Thus,...
Attentional, RNN-based encoder-decoder models for abstractive summarization have achieved good performance on short input and output sequences. However, for longer documents and summaries, these models often include repetitive and incohe... P Nema,MM Khapra,A Laha,... - Meeting of the Association...