Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: While several proactive acoustic feedback (Larsen-effect) cancellation schemes have been presented for speech applications with short acoustic feedback paths as encountered in hearing aids, these schemes fail with the long impulse responses inherent to, for instance, public address systems.  derive a new prediction error method (PEM)-based scheme (referred to as PEM-AFROW) which identifies both the acoustic feedback path and the nonstationary speech source model. A cascade of a short- and a long-term predictor removes the coloring and periodicity in voiced speech segments, which account for the unwanted correlation beten the loudspeaker signal and the speech source signal. The predictors calculate row operations which are applied to prewhiten the speech source signal, resulting in a least squares system that is solved recursively by means of normalized least mean square or recursive least squares algorithms. Simulations show that this approach is indeed superior to earlier approaches whenever long acoustic channels are dealt with
['Geert Rombouts', 'T. van Waterschoot', 'K. Struyve', 'Marc Moonen']
I am writing a research paper on a idea Acoustic feedback cancellation for long acoustic paths using a nonstationary source model
[{"from": "human", "value": "I am writing a research paper on a idea Acoustic feedback cancellation for long acoustic paths using a nonstationary source model"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: While several proactive acoustic feedback (Larsen-effect) cancellation schemes have been presented for speech applications with short acoustic feedback paths as encountered in hearing aids, these schemes fail with the long impulse responses inherent to, for instance, public address systems.  derive a new prediction error method (PEM)-based scheme (referred to as PEM-AFROW) which identifies both the acoustic feedback path and the nonstationary speech source model. A cascade of a short- and a long-term predictor removes the coloring and periodicity in voiced speech segments, which account for the unwanted correlation beten the loudspeaker signal and the speech source signal. The predictors calculate row operations which are applied to prewhiten the speech source signal, resulting in a least squares system that is solved recursively by means of normalized least mean square or recursive least squares algorithms. Simulations show that this approach is indeed superior to earlier approaches whenever long acoustic channels are dealt with"}]