# Synthesis of Non-Linguistic Utterances for Sound Design Support Using a Genetic Algorithm
### Related Work on Interpretation of NLUs  
Researchers have demonstrated the usefulness of NLUs for social robots. They can be applied to simple robots, robot pets, or toys that do not require complex speech [2], or even to location-tracking devices [10]. NLUs can also function independently of any specific language and are able to convey simple sentiments very rapidly [11]. Researchers [1; 3; 5; 6] have developed various methods of NLU generation for the expression of intention, emotion, and sometimes dialogue parts. Most have stopped after assessing the recognition rate of emotions from the sounds. This study introduces an automated technique for generating a broad array of NLU sounds that social robots can use naturally and dynamically to convey a wide spectrum of emotions. The method employs a genetic algorithm alongside a random forest model, which has been trained on a selection of representative non-speech sounds, to assess and ensure that each generated sound effectively communicates the intended emotion. [PERSON] [12] found that adults and children could interpret NLUs that conveyed four basic emotions: happiness, sadness, anger, and fear. The authors suggested that NLUs be used as an additional modality with visual cues and speech, rather than a replacement for them. The same authors [11] also discovered that children could easily interpret NLUs in terms of affect, such as happiness, sadness, anger, or fear, but they were not always consistent with each other. On the other hand, adults interpreted NLUs categorically and did not distinguish subtle differences between NLUs. Subsequently, [PERSON] [13] investigated how situational context influenced the interpretation of NLUs and found that it overrode NLU interpretation. The same NLU could be interpreted differently depending on the situational context, and when the situational context and NLU aligned, the interpretation was intensified. [PERSON] et al. [14] carried out a study to analyze the sounds from popular fictional robot characters from movies to determine key features that enable them to convey emotion. They defined specific important categorizations of sounds including the robot's inner workings, communication of movement, and conveying of emotion. They also suggested that the sounds used in films, having been designed for that purpose, inevitably lead to expectations from the audience regarding how robots should sound in the real world. The authors found that the long-term average spectrum (LTAS) effectively characterized robot sounds and the sonic characteristics of robots in films varied with their movements and physical appearance. Lastly, they observed that the sounds of the robots they studied used a wider range of frequencies than humans do when speaking. [PERSON] et al. [1] also studied the sounds of robots featured in popular films, namely R2D2 and WallE, with the aim of identifying the fundamental factors employed in conveying emotions and intentions. To accomplish this, the researchers devised a set of seven musical sounds, five for intentions, and two for emotions, which were evaluated using their English teaching robot Silbot. Among the parameters examined, intonation, pitch, and timbre emerged as the most prominent in effectively expressing emotions and intentions. The study established standard intonation and pitch contours while emphasizing the importance of crafting non-linguistic sounds that possess a universal quality, transcending any specific culture or language. Notably, the recognition rate experiment demonstrated that a combination of five sounds effectively conveyed intentions, while two sounds sufficed for emotions. The findings indicated that R2D2 relied on intonation and pitch to communicate emotion and intention, whereas WallE used pitch variation, intonation, and timbre to accentuate its communicative intentions. The timbre component represented the character of the speaker, with R2D2's metallic beeping nature symbolizing an honest, trustworthy persona.