Speaker identification is a crucial process that involves identifying the speaker in a recorded audio segment based on vocal characteristics, enabling accurate tagging of speakers in segmented audio files. Building an effective speaker identification system requires several subsystems, including speech detection, segmentation, embedding extraction, and clustering, which can be implemented using open-source packages like Resemblyzer or Spectral Clustering. Voiceprint recognition technology uses unique acoustic features to identify individuals, with sophisticated systems able to pinpoint speakers after fewer than ten words. Visual cues such as shot detection and facial recognition algorithms can provide additional data to help identify speakers in recorded video, while voice activity detection filters out non-speech inputs to improve accuracy. With the growing availability of conversational intelligence APIs, developers can easily incorporate speaker identification into their applications without building it from scratch.