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Recently, a hybrid deep neural network/i-vector framework has been proved effective for speaker verification, where the DNN trained to predict tied-triphone states (senones) is used to produce frame alignments for sufficient statistics extraction. In this work, in order to better understand the impact of different phonetic precision to speaker verification tasks, three levels of phonetic granularity...
Proxy-word based out of vocabulary (OOV) keyword search has been proven to be quite effective in keyword search. In proxy-word based OOV keyword search, each OOV keyword is assigned several proxies and detections of the proxies are regarded as detections of the OOV keywords. However, the confidence scores of these detections are still those of the proxies from lattices. To obtain a better confidence...
The National Digital Switching System Engineering and Technological R&D Center (NDSC) speech-to-text transcription system for the 2016 multi-genre broadcast challenge is described. Various acoustic models based on deep neural network (DNN), such as hybrid DNN, long short term memory recurrent neural network (LSTM RNN), and time delay neural network (TDNN), are trained. The system also makes use...
End-to-end speech recognition systems have been successfully implemented and have become competitive replacements for hybrid systems. A common loss function to train end-to-end systems is connectionist temporal classification (CTC). This method maximizes the log likelihood between the feature sequence and the associated transcription sequence. However there are some weaknesses with CTC training. The...
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