Speech plays a significant role in human interaction, yet machines struggle to understand emotions accurately. Real-time applications seek to integrate voice emotion recognition seems challenging for Indian languages like Gujarati. This study focuses on detailed information on Indian languages and importance of Gujarati language for constructing the Handcrafted Gujarati dataset also this paper covers literature review on available dataset in other Indian languages including Hindi, Marathi, Telugu, but for Gujarati it is still and emerging approach. We outline the steps, from corpus construction to feature extraction and selection techniques. By addressing this gap in Gujarati language speech emotion recognition, our research sets the stage for further advancements.