Speech recognition using neural networks - Chapter 9 pptx
Speech recognition using neural networks - Chapter 9 pptx
... 81– 89, 94 , 14 7-1 48 basic operation 81–82 training & testing procedures 8 2-8 4 experiments 8 4-8 7 extensions 8 9- 9 4 weaknesses 9 4 -9 9 vs. HMM 88– 89, 14 7-1 48 LVQ 33, 36, 39, 54, 75, 8 8-8 9, 14 7-1 48 M maximum ... Conference on Neural Networks, IEEE. [78] Lippmann, R. ( 198 9). Review of Neural Networks for Speech Recognition. Neural Computation...
Ngày tải lên: 13/08/2014, 02:21
Speech recognition using neural networks - Chapter 1 pot
... and so on, x Speech Recognition using Neural Networks Joe Tebelskis May 199 5 CMU-CS -9 5-1 42 School of Computer Science Carnegie Mellon University Pittsburgh, Pennsylvania 1521 3-3 890 Submitted ... tasks as voiced/unvoiced dis- crimination (Watrous 198 8), phoneme recognition (Waibel et al, 198 9), and spoken digit recognition (Franzini et al, 198 9). However, in 199 0,...
Ngày tải lên: 13/08/2014, 02:21
Speech recognition using neural networks - Chapter 2 docx
... though we are using it for speech recognition. The difference is moot. a ij 0 b i u( ) 0 i j u,,∀,≥,≥ a ij j ∑ 1 i∀,= b i u( ) u ∑ 1 i∀,= y 1 T 9 2. Review of Speech Recognition In this chapter we ... /ts/ 2. Review of Speech Recognition 26 2.3.4. Limitations of HMMs Despite their state-of-the-art performance, HMMs are handicapped by several well-known weaknesses, namely: • T...
Ngày tải lên: 13/08/2014, 02:21
Speech recognition using neural networks - Chapter 3 potx
... Delay Neural Network (TDNN), shown in Figure 3.8. This architecture was initially developed for phoneme recognition (Lang 198 9, Waibel et al 198 9), but it has also been applied to hand- writing recognition ... that the neural network may be simulated on a conventional computer, rather than imple- mented directly in hardware. 3. Review of Neural Networks 50 198 2) — or alternati...
Ngày tải lên: 13/08/2014, 02:21
Speech recognition using neural networks - Chapter 4 pps
... applied to phoneme recognition, not word recognition. Austin et al ( 199 2) at BBN explored true segment-level training for large vocabulary con- tinuous speech recognition. A Segmental Neural Network ... align- ment was shown to give better results. The DNN was applied to a Japanese database of iso- lated digits, and achieved 99 .3% word accuracy, outperforming pure DTW (98 .9% ). H...
Ngày tải lên: 13/08/2014, 02:21
Speech recognition using neural networks - Chapter 5 doc
... was developed in conjunction with the Janus Speech- to -Speech Translation system at CMU (Waibel et al 199 1, Osterholtz et al 199 2, Woszczyna et al 199 4). While a full discussion of Janus is beyond ... The speech recognition module, for exam- ple, was originally implemented by our LPNN, described in Chapter 6 (Waibel et al 199 1, Osterholtz et al 199 2); but it was later replaced b...
Ngày tải lên: 13/08/2014, 02:21
Speech recognition using neural networks - Chapter 6 pps
... (100%) 2 29/ 2 29 (100%) 3 50/50 (100%) 20/20 (100%) 2 29/ 2 29 (100%) 92 4 1 106/118 (90 %) 55/60 (92 %) 855 /90 0 (95 %) 2 116/118 (98 %) 58/60 (97 %) 886 /90 0 (98 %) 3 117/118 (99 %) 60/60 (100%) 891 /90 0 (99 %) Table ... consid- ered correctly recognized if it appears among the best K candidates. Vocab size Rank Testing set Training set Homophones Novel words 234 1 47/50 (94 %) 19/ 2...
Ngày tải lên: 13/08/2014, 02:21
Speech recognition using neural networks - Chapter 7 pdf
... labeling. Figure 7.14: A 3-state phoneme model outperforms a 1-state phoneme model. 80 82 84 86 88 90 92 94 96 98 100 word accuracy (%) 0 1 2 3 4 5 epochs 1-state vs 3-state models 1 state per ... training set. This important fact has been proven by Gish ( 199 0), Bourlard & Wellekens ( 199 0), Hampshire & Pearlmutter ( 199 0), Ney ( 199 1), and others; see Appendix B for detail...
Ngày tải lên: 13/08/2014, 02:21
Speech recognition using neural networks - Chapter 8 potx
... 402(b) 111 HMM-1 55% HMM-5 96 % 71% 58% 76% HMM-10 97 % 75% 66% 82% LPNN 97 % 60% 41% HCNN 75% LVQ 98 % 84% 74% 61% 83% TDNN 98 % 78% 72% 64% MS-TDNN 98 % 82% 81% 70% 85% Table 8.1: Comparative results ... testing criteria. It is with the MS-TDNN that we achieved a word recognition accuracy of 90 .5% using only 67K parameters, significantly outperforming the context inde- pendent HM...
Ngày tải lên: 13/08/2014, 02:21
speech recognition using neural networks
... Delay Neural Network (TDNN), shown in Figure 3.8. This architecture was initially developed for phoneme recognition (Lang 198 9, Waibel et al 198 9), but it has also been applied to hand- writing recognition ... performance. We will see that neural networks help to avoid this problem. 1.2. Neural Networks Connectionism, or the study of artificial neural networks, was initiall...
Ngày tải lên: 28/04/2014, 10:18