Application and Research of Big Data Speech Recognition System for Government Affairs System
The development of artificial intelligence and the advancement of intelligent government have put forward higher requirements for the timeliness of information processing in government systems.However,the current application of big data speech recognition systems in government systems is not mature enough,and there are many defects.Based on this,the research fused LSTM and CTC to obtain the LSTM-CTC acoustic model,and further optimized to obtain the BiLSTM-CTC acoustic model,while verifying its effectiveness.The experimental results show that the WER value of the BiLSTM-CTC model is 60.38%when the number of training rounds is 8;When the number of training rounds is 16,the WER value of the BiLSTM-CTC acoustic model is 11.87%,which is lower than the comparison model.At the same time,in actual government system big data speech recognition,the BiLSTM-CTC acoustic model has high recognition accuracy in both quiet and low noise environments,with an average recognition rate of 92.6%and 85%,respectively.In summary,the BiLSTM-CTC acoustic model has a high accuracy in identifying big data speech in government systems,and is of great significance in promoting the speech recognition function of actual government systems.
Government affairs systemBig dataSpeech recognition systemAcoustic model
万方数据
维普
