Connectionist Temporal Classification(CTC)[1] 是 Alex Graves 等人在 ICML 2006 上提出的一种端到端的 RNN 训练方法,它可以让 RNN 直接对序列数据进行学习,而无需事先标注好训练数据中输入序列和输入序列的映射关系,使得 RNN 模型在语音识别等序列学习任务中取得更好的效果,在语音识别和图像识别等领域 CTC 算法...
Code README MIT license Automatic speech recognition (ASR) system implementation that utilizes theconnectionist temporal classification (CTC)cost function. It's inspired by Baidu'sDeep Speech: Scaling up end-to-end speech recognitionandDeep Speech 2: End-to-End Speech Recognition in English and Mand...
connectionism (redirected fromConnectionist) con·nec·tion·ism (kə-nĕk′shə-nĭz′əm) n. The theory that thought, behavior, and especially learning can be explained and modeled by neural networks. con·nec′tion·istn.& adj. ...
1. The Decade of Long Short-Term Memory (LSTM) 长短时记忆网络的十年(LSTM) Much of AI in the 2010s was about the NN calledLong Short-Term Memory(LSTM)[LSTM1-13][DL4]. The world is sequential by nature, and LSTM has revolutionized sequential data processing, e.g., speech recognition,...
Furthermore, we also show how the batched forward-backward computation can be used to compute the gradients of the connectionist temporal classification (CTC) and maximum mutual information (MMI) losses with respect to the logits. We show, via empirical benchmarks, that the batched forward-...
Lab IDSIA: LSTM (1990s-2005)[LSTM1-6](which overcomes the famousvanishing gradient problemanalyzed by my PhD student Sepp Hochreiter[VAN1]in 1991) andConnectionist Temporal Classification[CTC](2006). CTC-trained LSTM was the first recurrent NN or RNN[MC43][K56]to win any international ...
The connectionist temporal classification (CTC) loss function has several interesting properties relevant for automatic speech recognition (ASR): applied o... Y Miao,M Gowayyed,X Na,... - IEEE International Conference on Acoustics 被引量: 41发表: 2016年 An Empirical Exploration of Countermeasures...
[CTC] A. Graves, S. Fernandez, F. Gomez, J. Schmidhuber. Connectionist Temporal Classification: Labelling Unsegmented Sequence Data with Recurrent Neural Networks. ICML 06, Pittsburgh, 2006.PDF. [GSR15] Dramatic improvement of Google's speech recognition through LSTM:Alphr Technology, Jul 2015, ...
This layer is responsible for translating the per-frame predictions into a final sequence according to the highest probability. These predictions are used to compute CTC or Connectionist Temporal Classification loss which makes the model learn and decode the output. ...
combination of two methods developed in my research groups at TU Munich and the Swiss AI Lab IDSIA: LSTM (1990s-2005) [LSTM1-6](which overcomes the famous vanishing gradient problem analyzed by my PhD student Sepp Hochreiter [VAN1] in 1991) and Connectionist Temporal Classification [CTC] (...