Auditory features for the close talk speech enhancement with parameter masks

The speech segregation and enhancement is a hard task in speech communication. In order to get the clean target speech, a close talk system is used to collect the speech with a nearby microphone. A deep neural networks (DNN) estimator is used in a frequency channel for speech energy calculation with parameter masks. The adjusted binaural auditory features are used as the main input for DNN speech energy estimation. The energy difference between the two microphones is used as the main binaural auditory feature. The time difference is also used as the comparison feature. Experiments show the energy difference feature can get the similar performance to the combination two microphones monaural and binaural auditory features with limited calculation complexity. The two microphones energy difference feature is one of the key features in close talk speech enhancement.