Dynamic adjustment of the forgetting factor in adaptive filters for non-stationary noise cancellation in speech

The field of speech recognition in noisy environments is of vital importance for the success of certain applications in the domain of communications, automation, avionics, and other harsh situations where common recognizers fail to meet acceptable standards due to the negative influence of environmental noise collected during the recording of the speech trace. To overcome such difficulties, adaptive filtering has been traditionally used with acceptable success in noise cancellation using two-microphone schemes. Some problems found in such situations are due to the non-stationary behavior of speech and noise, although the sudden changes in the energy levels of both speech and noise are the cause of frequent misadjustments and un-locking in the adaptive algorithms, rendering the task of noise cancellation a difficult one. Through the present paper, a method based on the continuous tracking of the energy differences between speech and noise is presented, which may be used for the dynamic adaptation of the forgetting factor in the adaptive filters, producing an effective control of the sudden changes in the signal/noise ratio. The paper discusses the proposed methods and shows some results from practical conditions. These results show good stability and a special ability for word-boundary detection under highly non-stationary conditions, especially useful in isolated word speech recognition