Development of Innovative Algorithm for Sound Detection Based on FFT and Goertzel Algorithms

The field of sound detection and analysis has witnessed remarkable advancements in recent years, driven by the increasing demand for applications such as speech recognition, environmental monitoring, and acoustic event detection. This work presents the development of an innovative algorithm for sound detection, leveraging the power of the Fast Fourier Transform (FFT) and Goertzel algorithms. The proposed algorithm combines the strengths of both the FFT and Goertzel algorithms to enhance the accuracy and efficiency of sound detection. The FFT is employed for its rapid transformation of time-domain audio signals into the frequency domain, providing valuable insights into the spectral characteristics of the input signal. Simultaneously, the Goertzel algorithm is applied to identify specific target frequencies with high precision and minimal computational overhead. This innovative approach addresses the limitations commonly associated with conventional sound detection algorithms, such as those relying solely on FFT or Goertzel. By harnessing the FFT's spectral analysis capabilities and the Goertzel algorithm's fine-grained frequency detection, the algorithm can effectively detect and classify sound events in various real-world scenarios.