Abstract: Method, system, and program product for measuring audio video synchronization. This is done by first acquiring audio video information into an audio video synchronization system. The step of data acquisition is followed by analyzing the audio information, and analyzing the video information. Next, the audio information is analyzed to locate the presence of sounds therein related to a speaker's personal voice characteristics. In Analysis Phase Audio and Video MuEv-s are calculated from the audio and video information, and the audio and video information is classified into vowel sounds including AA, EE, OO, B, V, TH, F, silence, other sounds, and unclassified phonemes. The inner space between the lips are also identified and determined. This information is used to determine and associate a dominant audio class in a video frame. Matching locations are determined, and the offset of video and audio is determined.

Abstract: Method, system, and program product for measuring audio video synchronization. This is done by first acquiring audio video information into an audio video synchronization system. The step of data acquisition is followed by analyzing the audio information, and analyzing the video information. Next, the audio information is analyzed to locate the presence of sounds therein related to a speaker's personal voice characteristics. The audio information is then filtered by removing data related to a speakers personal voice characteristics to produce a filtered audio information. In this phase filtered audio information and video information is analyzed, decision boundaries for Audio and Video MuEv-s are determined, and related Audio and Video MuEv-s are correlated. In Analysis Phase Audio and Video MuEv-s are calculated from the audio and video information, and the audio and video information is classified into vowel sounds including AA, EE, OO, silence, and unclassified phonemes.

Abstract: Method, system, and program product for measuring audio video synchronization. This is done by first acquiring audio video information into an audio video synchronization system. The step of data acquisition is followed by analyzing the audio information, and analyzing the video information. In this phase audio and video information is analyzed, decision boundaries for Audio and Video MuEv-s are determined, and related Audio and Video MuEv-s are correlated. In Analysis Phase Audio and Video MuEv-s are calculated from the audio and video information, and the audio and video information is classified into vowel sounds including AA, EE, OO, silence, and unclassified phonemes This information is used to determine and associate a dominant audio class in a video frame. Matching locations are determined, and the offset of video and audio is determined.

Abstract: Method, system, and program product for measuring audio video synchronization. This is done by first acquiring audio video information into an audio video synchronization system. The step of data acquisition is followed by analyzing the audio information, and analyzing the video information. Next, the audio information is analyzed to locate the presence of sounds therein related to a speaker's personal voice characteristics. In Analysis Phase Audio and Video MuEv-s are calculated from the audio and video information, and the audio and video information is classified into vowel sounds including AA, EE, OO, B, V, TH, F, silence, other sounds, and unclassified phonemes. The inner space between the lips are also identified and determined. This information is used to determine and associate a dominant audio class in a video frame. Matching locations are determined, and the offset of video and audio is determined.