Look who´s talking: speaker detection using video and audio correlation

The visual motion of the mouth and the corresponding audio data generated when a person speaks are highly correlated. This fact has been exploited for lip/speech-reading and for improving speech recognition. We describe a method of automatically detecting a talking person (both spatially and temporally) using video and audio data from a single microphone. The audio-visual correlation is learned using a time-delayed neural network, which is then used to perform a spatio-temporal search for a speaking person. Applications include videoconferencing, video indexing and improving human-computer interaction (HCI). An example HCI application is provided