By Tong Zhang, C.C. Jay Kuo
Content-Based Audio type and Retrieval for Audiovisual DataParsing is an up to date evaluation of audio and video content material research. incorporated is wide remedy of audiovisual information segmentation, indexing and retrieval in accordance with multimodal media content material research, and content-based administration of audio information. as well as the generally studied audio varieties equivalent to speech and song, the authors have incorporated hybrid kinds of sounds that include a couple of type of audio part similar to speech or environmental sound with song within the history. Emphasis can be put on semantic-level id and category of environmental sounds. The authors introduce a brand new widespread audio retrieval approach on best of the audio archiving schemes. either theoretical research and implementation matters are offered. The constructing MPEG-7 criteria are explored.
Content-Based Audio class and Retrieval for Audiovisual DataParsing could be particularly worthwhile to researchers and graduate point scholars designing and constructing absolutely practical audiovisual platforms for audio/video content material parsing of multimedia streams.
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Extra resources for Content-based audio classification and retrieval for audiovisual data parsing
5. The short-time fundamental frequency of audio signals: (a) t rumpet, (b) speech, (c) rain and (d) laugh. harmonic relations among the peaks. Compared to the problem of fundamental frequency estimation where the precision requirement is less strict and slight errors are allowed, the task here is more difficult in the sense that locations of tracks should be determined accurately. It should be the best that all tracks are detected without any artifact, which is very difficult to achieve. Nevertheless, with the confinement that only spectral peak tracks in song and speech segments are considered and based on distinct features ofsuch tracks as mentioned above, we derived a set of rules to pick up proper harmonic peaks.
If harmonic peaks are found in this spectrum, then we go on to the next signal frame. Otherwise, we will try the spectrum generated with the other two order levels. If no harmonic peaks were detected in the previous frame, we try the three order levels one by one for the current frame until harmonic peaks are found or the conclusion of no harmonic peaks existing is obtained. Harmonic peaks should have harmonic relations among them and satisfy some sharpness, amplitude, and width conditions. Since there are many spurious peaks in the spectrum generated with P = 80 or 100, we add the restriction that harmonic peaks should be aligned consecutively in the lower and middle frequency bands and that the fundamental frequency should be below 250Hz in such spectrum based on the feature of speech signals.
4 Keyframes of shots for soccer and basketball games from sports video. DOCUMENTARIES In documentary movies and videos, there are the structures of semantic scenes which are difficult to define simply by using audio and visual Video Content Modeling 27 features. However, with the help of audio clues, segmentation results can be much more improved than using the visual information alone. In such kind of video, audio parts are accompanied with pictorial parts off-line. Normally, there is music all through the program with commentary speech appearing from time to time.