Audio authentication plays a vital role in ensuring the integrity, authenticity, and security of digital audio data used in communication, multimedia, forensic analysis, and broadcasting applications. Conventional authentication methods often face challenges in detecting unauthorized modifications, noise interference, and signal distortions while maintaining computational efficiency. This paper presents a Digital Signal Processing (DSP)-based audio authentication system that verifies the authenticity of audio signals through efficient feature extraction and comparison techniques. The proposed methodology involves audio preprocessing, noise reduction, signal normalization, and extraction of distinctive spectral and temporal features using DSP algorithms. The extracted features are used to generate a unique authentication signature, which is securely compared with the reference signature to detect any tampering or unauthorized alterations. The system is designed to provide high authentication accuracy while maintaining low computational complexity, making it suitable for real-time implementation. Experimental evaluation demonstrates that the proposed DSP-based authentication approach effectively distinguishes authentic audio from manipulated recordings, exhibiting robustness against common signal processing operations such as compression, filtering, and additive noise. The proposed framework offers a reliable, efficient, and scalable solution for secure audio authentication in digital communication, multimedia security, and forensic applications.