Name
Abstract | ||
|---|---|---|
This paper investigates the problem of audio event detection and summarization, building on previous work [1, 2] on the detection of perceptually important audio events based on saliency models. We lake a synergistic approach to audio summarization where saliency computation of audio streams is assisted by using the text modality as well. Auditory saliency is assessed by auditory and perceptual cues such as Teager energy, loudness and roughness; all known to correlate with attention and human hearing. Text analysis incorporates part-of-speech tagging and affective modeling. A computational method for the automatic correction of the boundaries of the selected audio events is applied creating summaries that consist not only of salient but also meaningful and semantically coherent events. A non-parametric classification technique is employed and results are reported on the MovSum movie database using objective evaluations against ground-truth designating the auditory and semantically salient events. |
Year | Venue | Keywords |
|---|---|---|
2015 | European Signal Processing Conference | monomodal auditory saliency,affective text analysis,audio-text salient events,audio summarization |
Field | DocType | ISSN |
Loudness,Automatic summarization,Computer science,Salience (neuroscience),Audio mining,Feature extraction,Speech recognition,Perception,Semantics,Salient | Conference | 2076-1465 |
Citations | PageRank | References |
1 | 0.35 | 21 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Athanasia Zlatintsi | 1 | 46 | 4.49 |
| Elias Iosif | 2 | 155 | 16.65 |
| Petros Maragos | 3 | 3733 | 591.97 |
| Alexandros Potamianos | 4 | 1443 | 149.05 |