Vocal emotion production is a complex form of motor control, is a crucial feature of social communication, and plays a main role in emotion theories. In recent literature, emotion has been considered to emerge from the dynamic interplay between motor and sensory components. Vocal emotion production is therefore a useful way to further investigate the motor components of emotions. Following the framework of embodied emotions, the research on vocal emotion production, besides shedding light on the mechanisms of emotion expression, is an important step toward understanding social communication given its connection with understanding others' emotions. Furthermore, despite there is considerable research on the perception of vocal emotions; a limited amount of the literature has examined vocal emotion production. We addressed this problem by investigating the temporal and motor dynamics of vocal emotion production (anger, joy, neutral) using time-frequency analysis of electroencephalographic data (EEG). The task of the participants was to express five selected pseudowords with different motor production properties, such as “pronounce”, “articulate” or “imagine”, in an angry, joyful, or neutral manner. Our results highlighted emotion-specific and motor-specific effects of such vocalisations in the domain of synchronization and desynchronization of event-related oscillations in the mu (8-12 Hz) and gamma (55-100 Hz) band. We observed significant differences in mu rhythm event-related desynchronization (ERD) and gamma event-related synchronization (ERS) for (1) joy vs anger and (2) emotion vs neutral. Although for the mu rhythm desynchronization in the imagine condition we did not observe an emotion-specific effect, the ERDs were still present. On the other hand, for the gamma-event related synchronization, we observed significantly different ERS in all expression and emotion conditions. These results are in line with previous studies suggesting that gamma ERS is closely related to emotions. Moreover, since in the imagine condition, there is no feedback and no difference in the mu rhythm ERD, while there were mu rhythm ERD differences detected between emotions in conditions that have feedback properties, these differences in mu rhythm might signify the distinct sensorimotor characteristics related to feedforward and feedback control. Further research with a larger sample size is needed to clarify the difference between emotions and their motor properties in expression and perception domains, as well as to investigate the underlying brain structures and the differences in electrophysiological correlates of vocal emotion production in clinical populations with emotional and motor deficits.