Name
Title | ||
|---|---|---|
A Generic Audio Identification System for Radio Broadcast Monitoring Based on Data-Driven Segmentation |
Abstract | ||
|---|---|---|
In this paper, a generic audio identification system is introduced to identify advertisements and songs in radio broadcast streams using automatically acquired segmental units. A new fingerprinting method based on ALISP data-driven segmentation is presented. A modified BLAST algorithm is also proposed for fast and approximate matching of ALISP sequences. To detect commercials and songs, ALISP transcriptions of references composed of large library of commercials and songs, are compared to the transcriptions of the test radio stream using Levenshtein distance. The system is described and evaluated on broadcast audio streams from 12 French radio stations. For advertisement identification, a mean precision rate of 100% with the corresponding recall value of 98% were achieved. For music identification, a mean precision rate of 100% with the corresponding recall value of 95% were achieved. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ISM.2012.87 | Multimedia |
Keywords | Field | DocType |
music identification,corresponding recall value,generic audio identification system,alisp data-driven segmentation,data-driven segmentation,advertisement identification,french radio station,radio broadcast stream,alisp transcription,radio broadcast monitoring,mean precision rate,alisp sequence,audio signal processing,radio broadcasting,music | Radio broadcasting,Transcription (linguistics),Broadcasting,Data-driven,Pattern recognition,Computer science,Segmentation,Identification system,Levenshtein distance,Speech recognition,Artificial intelligence,Audio signal processing | Conference |
ISBN | Citations | PageRank |
978-1-4673-4370-1 | 1 | 0.44 |
References | Authors | |
8 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Houssemeddine Khemiri | 1 | 27 | 4.14 |
| Dijana Petrovska-Delacretaz | 2 | 57 | 6.98 |
| Gerard Chollet | 3 | 12 | 2.08 |