<p>The G.723 audio codec is a popular speech compression standard for low-bitrate voice transmission over communication systems. However, error concealment mechanisms can introduce distortions that affect speech intelligibility. To address this, the paper proposes Enhanced Speech Recognition in G.723 Audio Codec using Mahalanobis Distance-Based Error Resilience and Concealment (ESR-MD-ER). The Mahalanobis Distance (MD) technique identifies errors between received audio and anticipated values based on the original signal characteristics of the codec. Errors detected by MD are then corrected by Adaptive Error Concealment (AEC), with optimal performance added without extra delays or audio loss. This paper introduces a new approach to enhancing speech recognition accuracy and audio quality in the G.723.1 codec using MD-based concealment and error resilience. The method identifies and compensates for distortions over a range of Bit Error Rates (BER), sustaining intelligibility and ensuring audio continuity in speech and music. Thorough waveform inspection and regulated BER testing (2–40%) confirm the tolerance of the suggested system. Through the utilization of MD’s perturbation sensitivity, the technique tunes error detection and concealment well, performing better than Euclidean, Chebyshev, and Canberra measures in precision and reconstruction. Comparative outcomes reflect improved RMSE, PSNR, and MAE, precision, accuracy performance in mixed audio environments. Even with its greater computational complexity (O(n²)), the Mahalanobis-based approach is worth it to achieve effective error reduction.</p>