The study of how to identify and translate feelings between different languages is expanding rapidly. As more people become interested in the study of speech signals, numerous methods have been created to decipher the tone of a speaker's words. Traditional speech analysis and classification methodologies are just two of the many tools used in speech emotion identification research (SER). This report provides a comprehensive overview of the research on multilingual and multimodal speech emotion recognition. Limitations of speech emotion detection, speech emotion extraction methods, speech emotion databases, and contributions from speech emotion extraction are discussed. The goal of these articles was to assess the state of multilingual and multimodal speech emotion detection in Scopus relative to current trends and leading countries in this field of study. The search syntax is based on language and medium-agnostic voice emotion recognition. In our essay, we summarise the research conducted over the past decade. Voice emotion detection and multilingual and multimodal were used to locate 706 records in Scopus between January 1, 2013, and October 23, 2022. The VOS viewer programme was then used to evaluate these files.