Voice talks can modify acoustic structures of speech, which may affect the operation of mistreatment models to affect people with attypical talk. We examine publicly available models to recognize that they are careful to contact talks from addressing attypical talk data, which compares the results to regular speech dattasets. We investigate the size of three ATYPCALITY: Corruption, Relationships; Monopitch, related to pososy, and harsh, related to the quality of voice. We look at (1) Distribution of division distribution conditions affecting predicting within the data, (2) comparing the same speculative designation affecting the same technical datasets such as speech and talking about effective Valience and renewal talk. We find that touching consequences have a great influence on the existence and quality of attypitite talks. For example, the foretold phrase percent as it tragicly tragicly in all kinds and attypical marks compared to similar typical communication details. In the first investigation of the Attypical talk, we find well organized models in pseudo -led models Aypicical Details Attypica develops attypical talk without touching a common talk. Our results emphasize the need for comprehensive training and the assessment of the speaking emotions, and the powerful model methods of the differences in voice and speech.
