An audio classifier that can distinguish between speech, music, silence and garbage has been developed. The classifier was trained and tested on broadcast news material provided by VRT (Flemish Radio and Television Network). Several feature sets and machine learning algorithms have been tested, providing choices of speed and performance for a target system. The audio classifier is part of a greater system that together with visual data can retrieve information from news broadcasts: speech can be converted to text and the speaker can be recognized. Music can be further used for genre classification, jingle recognition or copyright infringement detection. Silence is recognized and used to provide cues on topic changes or speaker turns. At this point everything that is not classified as speech, music or silence is labeled garbage. Garbage classes can be further used for background categorization giving information on the environment where someone speaks (an anchor in the studio or a reporter in the street).
['Yorgos Patsis', 'Werner Verhelst']
A Speech/Music/Silence/Garbage/ Classifier for Searching and Indexing Broadcast News Material