Title :
A novel recurrent network based pitch detection technique for quasi-periodic/pitch-varying signals
Author :
Chang, Wei-Chen ; Su, Alvin W Y
Author_Institution :
Dept. of Comput. Sci. & Ing. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
fDate :
6/24/1905 12:00:00 AM
Abstract :
The accuracy of pitch detection algorithms affects the performance of many speech and audio applications such as speech compression, computer music analysis/synthesis and information retrieval of audio signals. In many applications, it is also desired that the algorithms should be robust to background noise. A recurrent network based method is proposed in this paper. Though the proposed method requires more computation compared to some existing methods, it is more accurate and less sensitive to noise. The other advantage is that it requires a smaller time frame to estimate the pitch compared to other methods. Therefore, it is more suitable for tracking the pitch of a pitch-varying signal or a quasi-periodic signal. Both the synthesized and natural tones are used in the computer simulation
Keywords :
function approximation; learning (artificial intelligence); recurrent neural nets; speech processing; speech recognition; audio signals; background noise reduction; function approximation; learning algorithm; pitch detection; quasi-periodic signal; recurrent neural network; speech recognition; Algorithm design and analysis; Application software; Detection algorithms; Information analysis; Music; Performance analysis; Signal analysis; Signal synthesis; Speech analysis; Speech synthesis;
Conference_Titel :
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7278-6
DOI :
10.1109/IJCNN.2002.1005579