Title :
A robust howling detection algorithm based on a statistical approach
Author :
Flocon-Cholet, Joachim ; Faure, Julien ; Guerin, Alexandre ; Scalart, Pascal
Author_Institution :
Orange Labs., Lannion, France
Abstract :
This paper presents an algorithm for the detection of howlings that arise in audio signals. Our method is based on the combination of two energy-based features and one new feature related to the frequency stability of a howling component. The decision stage, which implies a Support Vector Machine (SVM) model, outputs a decision every 20 ms. The evaluation, carried out on a large database, showed that the algorithm is able to detect both pure and multiple tones howling in a wide range of energy. Furthermore, even on complex signals such as music, the detection is still efficient with very few false alarms.
Keywords :
acoustic signal detection; audio signal processing; statistical analysis; support vector machines; audio signal; energy based feature; frequency stability; howling component; robust howling detection algorithm; statistical methods; support vector machine; Acoustics; Hidden Markov models; Multiple signal classification; Speech; Support vector machines; Time-frequency analysis; Training; Acoustic signal detection; Howling detection;
Conference_Titel :
Acoustic Signal Enhancement (IWAENC), 2014 14th International Workshop on
Conference_Location :
Juan-les-Pins
DOI :
10.1109/IWAENC.2014.6953339