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corpus. Using a bigram phoneme language model, phoneme recognition experiments are performed on a two hour independent test set using the Viterbi decoding which show a relative 33.3% improvement by our CD-DNN acoustic model. We then present a filler based Hybrid DNN-HMM Keyword Spotting KWS system which to our knowledge is
For text-query-based keyword spotting from handwritten Chinese documents, the index is usually organized as a candidate lattice to overcome the ambiguity of character segmentation. Each edge in the lattice denotes a candidate character associated with a candidate class. Character similarity (between character and
This paper proposes a method for keyword spotting in offline Chinese handwritten documents using a statistical model. On a text query word, the method measures the similarity between the query word and every candidate word in the document by combining a character classifier and four classifiers characterizing the
The paper deals with the development of acoustic keyword spotter (KWS) meeting requirements of a real user from the security community. While the basic scheme of the KWS is relatively standard, it uses novel features derived by a hierarchy of neural networks, and score normalization trained to maximize a user-like
We propose a max-pooling based loss function for training Long Short-Term Memory (LSTM) networks for small-footprint keyword spotting (KWS), with low CPU, memory, and latency requirements. The max-pooling loss training can be further guided by initializing with a cross-entropy loss trained network. A posterior
This paper proposes a novel system for robust keyword detection in continuous speech. Our decoder is composed of a bidirectional Long Short-Term Memory recurrent neural network using a Connectionist Temporal Classification (CTC) output layer, and a Dynamic Bayesian Network (DBN). The CTC network exploits bidirectional
This work proposes a voice-activity home care system which can construct a life log associated with voices at home. Accordingly, the techniques of sound-pressure-level calculation, abnormal sound detection, noise reduction, text-independent speaker recognition and keyword spotting are developed. In abnormal sound
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