کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
569006 | 876514 | 2006 | 10 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Hybrid NN/HMM acoustic modeling techniques for distributed speech recognition Hybrid NN/HMM acoustic modeling techniques for distributed speech recognition](/preview/png/569006.png)
Distributed speech recognition (DSR) where the recognizer is split up into two parts and connected via a transmission channel offers new perspectives for improving the speech recognition performance in mobile environments. In this work, we present the integration of hybrid acoustic models using tied-posteriors in a distributed environment. A comparison with standard Gaussian models is performed on the AURORA2 task and the WSJ0 task. Word-based HMMs and phoneme-based HMMs are trained for distributed and non-distributed recognition using either MFCC or RASTA-PLP features. The results show that hybrid modeling techniques can outperform standard continuous systems on this task. Especially the tied-posteriors approach is shown to be usable for DSR in a very flexible way since the client can be modified without a change at the server site and vice versa.
Journal: Speech Communication - Volume 48, Issue 8, August 2006, Pages 1037–1046