Multimedia Content Segmentation Based on Speaker Recognition

Many recent works attempt to index multimedia data based on characteristics such as speaker identity and emotional content. In this work, speaker segmentation is performed on movies to extract the shots in which the target actor is speaking. A case of speaker identification on conversational speech under noisy conditions-this work is organized into two phases; an audio classification phase, for the removal of non-speech content, followed by a speaker recognition phase. Along with the speaker models, Gaussian mixture models are constructed for sound effects like fight sequences and drum beats to refine the removal of non-speech sounds. Results prove the effectiveness of this deviation from the conventional methods