Lecture presented by Hervé Bredin (IRIT).
This course introduces basis knowledge on speech segmentation. Processing a full recording, obtained for instance from a TV or radio show, requires to identify specific segments of the audio signal. In order to have clean speech with a single speaker, the presence of noise, speech and overlapping speech needs to be precisely determined under a segmentation task. Then, speaker diarization is the task of partitioning an audio stream into homogeneous temporal segments according to the identity of the speaker (i.e. answering the question "who speaks when?"). During the day, we will present the speech segmentation by classification approach and the speaker diarization process.