Title :
An improved phase-space voicing-state classification for co-channel speech based on pitch detection
Author :
Guo, Haiyan ; Shao, Xi ; Yang, Zhen
Author_Institution :
Inst. of Signal Process. & Transm., Nanjing Univ. of Posts & Telecommun., Nanjing
Abstract :
This paper presents an improved phase-space voicing state classification method based on pitch detection to simultaneously determine the voicing state of two speakers present in a segment of co-channel speech. Three possible voicing states are considered: Unvoiced/Unvoiced (U/U), Voice/Unvoiced (V/U), Voiced/Voiced (V/V). Firstly, the method employs a phase-space voicing-state classification algorithm to classify co-channel speech into three parts: U/U frames, V/U frames and V/V frames. Secondly, in order to decrease misjudgment between V/U and V/V frames, we introduce mulitpitch detection based on enhanced summary autocorrelation function (ESACF) to modify the voicing states of V/V frames and single pitch detection based on autocorrelation function (ACF) to modify the voicing states of V/U frames. Experiments show the proposed method effectively reduces the classification error rate and outperforms the voicing-state classification algorithm only based on phase-space reconstruction.
Keywords :
phase space methods; speech recognition; co-channel speech; enhanced summary autocorrelation function; mulitpitch detection; phase-space voicing-state classification; Autocorrelation; Bayesian methods; Classification algorithms; Educational institutions; Error analysis; Phase detection; Signal processing; Signal processing algorithms; Speech processing; Training data;
Conference_Titel :
Signal Processing, 2008. ICSP 2008. 9th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2178-7
Electronic_ISBN :
978-1-4244-2179-4
DOI :
10.1109/ICOSP.2008.4697222