Wideband software-defined radio (SDR) applications include data and time intensive operations such as wideband spectrum, signal detection, digital down conversion (DDC), and analog demodulation. Each of these processes need to be performed in order to produce the audio signal from the wideband signals. However, serial implementation of SDR applications do not provide necessary rate speed to obtain the sound and speech data in real time. In this work, we propose a real time SDR implementation using a heterogeneous architecture with CPUs and GPUs. To obtain the sound and speech data from the signals received and processed in SDR algorithms in real time, we also provide necessary optimizations. We test the proposed design using both single CPU core, multiple CPU cores, and GPUs. High performance is observed with our proposed algorithm in experimental tests. We also provide test results in a mobile setup where resources such as power and size are limited. For this purpose, we provide test results on NVIDIA Jetson GPUs and portable laptop CPUs. This work shows a proof of concept that the sound of a signal can be detected in the wideband spectrum and can be played back continuously in a real time with the help of the parallel programming suitable for low power consumption.