TY  - JOUR
T1  - An Adaptively Enhanced Auditory Transform Based Feature Extraction Algorithm for Robust Speaker Identification
AU - Umarani, S.D. AU - Wahidabanu, R.S.D. AU - Raviram, P. 
JO  - International Journal of Soft Computing
VL  - 8
IS  - 1
SP  - 56
EP  - 62
PY  - 2013
DA  - 2001/08/19
SN  - 1816-9503
DO  - ijscomp.2013.56.62
UR  - https://makhillpublications.co/view-article.php?doi=ijscomp.2013.56.62
KW  - Robust speech recognition
KW  -auditory transform
KW  -adaptive enhancement
KW  -cochlear
KW  -filter bank
KW  -CFCC
AB  - In speech recognition systems, obtaining good performance 
  in noisy environments still remains a very challenging task. The problem is 
  that recognition accuracy degrades significantly if training conditions are 
  not matched to the corresponding test conditions. This study uses auditory transform 
  along with CFCC (Cochlear Filter Cepstral Coefficients). Usually, the performance 
  of acoustic models trained in clean speech drops significantly when tested in 
  noisy speech. The CFCC features have shown strong robustness in this kind of 
  situation. The auditory transform replaces the STFT in CFCC for overcoming the 
  STFT’s disadvantage of fixed time-frequency resolution. Thus, a kind of 
  good anti-noisy speech feature coefficient was obtained. In order to enhance 
  the ability to resist the noises of different environments, an adaptive enhancement 
  approach is introduced. The CFCC features with wavelet are applied to a speaker 
  identification task to address the acoustic mismatch problem between training 
  and testing environments. Finally, this experimental results show that noise 
  resilience of the proposed method under small samples circumstance is better 
  than exiting methods at least by 3 dB in worsetcase for lesser word count and 
  at least 1 dB for larger word count. It is observed that CFCC feature with adaptive 
  enhancement can remain better robust to noise. And its performance is more effective 
  under low SNRs. It makes the speech recognition become possible under these 
  conditions.
ER  -