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Automaticspeechrecognition(ASR)tasksareresolvedbyend-to-enddeeplearningmodels,whichbenefitsusbylesspreparationofrawdata,andeasiertransformationbetweenlanguages.Weproposeanovelend-to-enddeeplearningmodelarchitecturenamelycascadedCNN-resBiLSTM-CTC.Intheproposedmodel,weaddresidualblocksinBiLSTMlayerstoextractsophisticated…
Inthispaper,phoneticfeaturesderivedfromthejointacousticmodel(JAM)ofamultilingualendtoendautomaticspeechrecognitionsystemareproposedforIndianlanguageidentification(LID).ThesefeaturesutilizecontextualinformationlearnedbytheJAMthroughlongshort-termmemory-connectionisttemporalclassification(LSTM-CTC)framework.Hence,thesefeaturesarereferredtoas...
论文《End-to-endSequenceLabelingviaBi-directionalLSTM-CNNs-CRF》的代码实现CNN卷积神经网络实现语音识别.zip目的：使用CNN卷积神经网络实现语音识别步骤：（1）预处理。首尾端的静音切除，降低对后续步骤造成的干扰，然后进行声音分帧，把...
Automaticspeechrecognition(ASR)tasksareresolvedbyend-to-enddeeplearningmodels,whichbenefitsusbylesspreparationofrawdata,andeasiertransformationbetweenlanguages.Weproposeanovelend-to-enddeeplearningmodelarchitecturenamelycascadedCNN-resBiLSTM-CTC.Intheproposedmodel,weaddresidualblocksinBiLSTMlayerstoextractsophisticated…
Inthispaper,phoneticfeaturesderivedfromthejointacousticmodel(JAM)ofamultilingualendtoendautomaticspeechrecognitionsystemareproposedforIndianlanguageidentification(LID).ThesefeaturesutilizecontextualinformationlearnedbytheJAMthroughlongshort-termmemory-connectionisttemporalclassification(LSTM-CTC)framework.Hence,thesefeaturesarereferredtoas...
论文《End-to-endSequenceLabelingviaBi-directionalLSTM-CNNs-CRF》的代码实现CNN卷积神经网络实现语音识别.zip目的：使用CNN卷积神经网络实现语音识别步骤：（1）预处理。首尾端的静音切除，降低对后续步骤造成的干扰，然后进行声音分帧，把...
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