Purpose: In this article, the authors describe and validate the performance of a modern acoustic analyzer specifically designed for infant cry analysis. Method: Utilizing known algorithms, the authors developed a method to extract acoustic parameters describing infant cries from standard digital audio files. They used a frame rate of 25 ms with a frame advance of 12.5 ms. Cepstral-based acoustic analysis proceeded in 2 phases, computing frame-level data and then organizing and summarizing this information within cry utterances. Using signal detection methods, the authors evaluated the accuracy of the automated system to determine voicing and to detect fundamental frequency (F[subscript 0]) as compared to voiced segments and pitch periods manually coded from spectrogram displays. Results: The system detected F[subscript 0] with 88% to 95% accuracy, depending on tolerances set at 10 to 20 Hz. Receiver operating characteristic analyses demonstrated very high accuracy at detecting voicing characteristics in the cry samples. Conclusions: This article describes an automated infant cry analyzer with high accuracy to detect important acoustic features of cry. A unique and important aspect of this work is the rigorous testing of the system's accuracy as compared to ground-truth manual coding. The resulting system has implications for basic and applied research on infant cry development.