As micro air vehicles (MAVs) become increasingly integrated into various applications, the need for intuitive control mechanisms becomes paramount. Voice commands present a promising interface, offering hands-free and natural interaction with MAVs. However, ensuring the accuracy and reliability of voice command systems is critical for safe and effective operations. The paper presents an evaluation framework designed to assess the performance of voice command systems in controlling MAVs. The framework incorporates advanced techniques, including Automatic Speech Recognition (ASR) and Natural Language Processing (NLP), to interpret spoken commands and provide contextual understanding. Additionally, a command validity assessment framework is developed to enhance safety by evaluating the reliability of recognized commands. The integration of confidence scores from ASR and semantic analysis along with contextual clue from NLP further improves the robustness of the system. The effectiveness of the proposed framework is demonstrated through experimental evaluation, highlighting improvements in accuracy, reliability, and adaptability. The paper contributes to the development of more effective and reliable voice command systems for controlling MAVs, paving the way for their seamless integration into various applications.