As digitization is continuously going to be increased, the representation of signal, its communication, storage and processing have been rapidly shifted in to digital landscape instead of analog landscape. With the advent & rapid proliferation of Digital Signal Processing devices, it is highly desirable to process much of the signal in software in digital domain, so as to reduce the analog front end & component count. An important & widely used process on signals is filtering, which is required in numerous applications. Digital filters are widely classified as Finite Impulse Response (FIR) and IIR Infinite Impulse Response (IIR) Filters, where IIR Filters with some number of coefficients exhibit more advantages over FIR Filter, however IIR filters provide some disadvantages like complex design and multimodal noise. In the present work, an Auto Adoptive IIR Filter has been developed using hybrid techniques. This hybrid technique has been composed by integrating or combining the P^th Norm Optimization with Artificial Neural Network (ANN). These two techniques have been used in such a way that the filter is designed using P^th Norm Optimization algorithm and filter's coefficients have been auto adapted using Artificial Neural Network to achieve the desired results. The simulation work is obtained using MATLAB and realtime audio capture, filtering and playback are demonstrated.