document: Speaker adaptive modeling by vocal tract normalization This paper presents methods for speaker adaptive modeling using vocal tract normalization -LRB- VTN -RRB- along with experimental tests on three databases . We propose a new training method for VTN : By using single-density acoustic models per HMM state for selecting the scale factor of the frequency axis , we avoid the problem that a mixture-density tends to learn the scale factors of the training speakers and thus can not be used for selecting the scale factor . We show that using single Gaussian densities for selecting the scale factor in training results in lower error rates than using mixture densities . For the recognition phase , we propose an improvement of the well-known two-pass strategy : by using a non-normalized acoustic model for the first recognition pass instead of a normalized model , lower error rates are obtained . In recognition tests , this method is compared with a fast variant of VTN . The two-pass strategy is an efficient method , but it is suboptimal because the scale factor and the word sequence are determined sequentially . We found that for telephone digit string recognition this suboptimality reduces the VTN gain in recognition performance by 30 % relative . In summary , on the German spontaneous speech task Verbmobil , the WSJ task and the German telephone digit string corpus SieTill , the proposed methods for VTN reduce the error rates significantly
doc_bio_tags: B I I O B I I O O O O O B I I O B I I O O O O O O O O O B O O O O O B I O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O B I I O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O B I I I O O O O O O O O O O O O O O O O O O O B I I I O O O B I O O B I I I I B O O O O O O O O O O O
extractive_keyphrases: speaker adaptive modeling vocal tract normalization databases training method hmm state training speakers single gaussian densities training results nonnormalized acoustic model word sequence telephone digit string recognition german spontaneous speech task wsj task german telephone digit string corpus sietill
abstractive_keyphrases: single-density acoustic models frequency scale factor error rate reduction two-pass strategy verlimobil