Cepstrum-Based Preprocessing for Howling Detection in Speech Applications

Peng R, Li J, Zheng C, Chen X, Li X. Cepstrum-Based Preprocessing for Howling Detection in Speech Applications. In: AES Convention 135. Audio Engineering Society; 2013. Paper 8978. Available from: https://aes.org/publications/elibrary-page/?id=17026

@inproceedings{Peng2013_17026,
  author = {Peng, Renhua and Li, Jian and Zheng, Chengshi and Chen, Xiaoliang and Li, Xiaodong},
  title = {{Cepstrum-Based Preprocessing for Howling Detection in Speech Applications}},
  booktitle = {AES Convention 135},
  note = {Paper 8978},
  year = {2013},
  month = oct,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=17026}
}

TY  - CPAPER
TI  - Cepstrum-Based Preprocessing for Howling Detection in Speech Applications
AU  - Peng, Renhua
AU  - Li, Jian
AU  - Zheng, Chengshi
AU  - Chen, Xiaoliang
AU  - Li, Xiaodong
T2  - AES Convention 135
M1  - Paper 8978
PY  - 2013
DA  - 2013/10/06
UR  - https://aes.org/publications/elibrary-page/?id=17026
PB  - Audio Engineering Society
LA  - en
AB  - Conventional howling detection algorithms exhibit dramatic performance degradations in the presence of harmonic components of speech that have the similar properties with the howling components. To solve this problem, this paper proposes a cepstrum preprocessing-based howling detection algorithm. First, the impact of howling components on cepstral coefficients is studied in both theory and simulation. Second, according to the theoretical results, the cepstrum pre-processing-based howling detection algorithm is proposed. The Receiver Operating Characteristic (ROC) simulation results indicate that the proposed algorithm can increase the detection probability at the same false alarm rate. Objective measurements, such as Speech Distortion (SD) and Maximum Stable Gain (MSG), further confirm the validity of the proposed algorithm.
ER  -