Voice and language analysis through artificial intelligence has become a promising field in diagnosing mental illnesses. This field relies on analyzing speech patterns, tone of voice, speech speed, and the content of language used by patients to detect psychological disorders such as depression, anxiety, and schizophrenia.<br /><br />Through deep learning techniques, AI can process audio and linguistic data to detect subtle changes that may go unnoticed by doctors in traditional assessments. For example, research has shown that people with depression often use words that express sadness or isolation, while schizophrenia patients may experience changes in sentence structure and speech speed.<br /><br />Moreover, machine learning techniques can be used to compare patient data with previous records, helping provide an accurate assessment of the progression of mental illness and the likelihood of its worsening. These systems also enable tracking linguistic and vocal changes over time, offering a comprehensive view of the patient's psychological state.<br /><br />Despite significant advancements in this field, challenges remain regarding diagnostic accuracy, patient privacy protection, and the need to confirm results through additional clinical examinations. However, voice and language analysis through AI holds great potential for improving early diagnosis of mental illnesses, enabling doctors to provide appropriate treatments at the right time.<br /><br />As these technologies evolve, AI could become an effective tool not only in detecting psychological disorders at early stages but also in monitoring patients' conditions over time and offering insights that may help develop new therapeutic approaches.<br /><br />Al-Mustaqbal University is the first University in Iraq.