Applying Hidden Markov Model Baby Cry Signal Recognition Based on Cybernetic Theory
Baby cry signal recognition is branch of application of speech recognition. It studied trans lation of cry signal into text. Using tool to pick up a short time period from a signal, the tools can still assume the signa l under processing to be stationary. It may constitute time invariant system and time invariant excitation when it is viewed in blocks of 10 30 msec. A processing is termed as Short Term Processing (STP) Then, using melfrequency cepstral coefficients (MFCC) and bark frequency cepstral coe fficients (BFCC) extract the feature of different known baby cry signal to make the codebook. Set up hidden markov m o (HMM) to train estimate baby cry signal. Classify estimate baby cry achieve baby cry signal recognition.