  Speaker individuality information is among the most critical elements within
speech signals. By thoroughly and accurately modeling this information, it can
be utilized in various intelligent speech applications, such as speaker
recognition, speaker diarization, speech synthesis, and target speaker
extraction. In this article, we aim to present, from a unique perspective, the
developmental history, paradigm shifts, and application domains of speaker
modeling technologies within the context of deep representation learning
framework. This review is designed to provide a clear reference for researchers
in the speaker modeling field, as well as for those who wish to apply speaker
modeling techniques to specific downstream tasks.
