Stuttering Detection and Severity Assessment Based on Faster-Rcnn-Fpn Algorithm
At present,the detection of stuttering in China is mainly through the subjective evaluation of language experts,and there is a lack of intelligent and objective medical aids to detect the severity of stuttering.In response to this phenomenon,this pa-per evaluates the severity of children's stuttering based on the UClass stuttering corpus,and uses the Faster-Rcnn-Fpn deep learn-ing algorithm to detect the spectrogram.The experimental results show that the model can effectively detect stuttering speech repeti-tion,prolongation and interjection types,and calculate the language efficiency score(SES)according to its duration to express the severity of stuttering.It is expected to become a medical auxiliary tool for calculating and analyzing the severity of stuttering,which is convenient for early detection of children's stuttering disorder and helps children's physical and mental development.
deep learningFaster-Rcnn-Fpn algorithmstutteringobject detectionspectrogram recognition
万方数据
维普
