Speech, Audio, Image and Biomedical Signal Processing using by Deniz Erdogmus, Umut Ozertem, Tian Lan (auth.), Bhanu

By Deniz Erdogmus, Umut Ozertem, Tian Lan (auth.), Bhanu Prasad, S. R. Mahadeva Prasanna (eds.)

Humans are awesome in processing speech, audio, photograph and a few biomedical signs. man made neural networks are proved to achieve success in acting a number of cognitive, commercial and clinical initiatives. This peer reviewed publication provides a few contemporary advances and surveys at the functions of synthetic neural networks within the parts of speech, audio, snapshot and biomedical sign processing. It includes 18 chapters ready by way of a few reputed researchers and practitioners round the globe.

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49 No. 11 End (f0 Hz) Fig. 5. 75 Frames X10 1 0 0 1 0 0 1 0 0 1 H 0 1 0 0 1 0 0 1 0 0 M Output fields 0 0 1 0 0 1 0 0 1 0 L 34 ` ad´ı O O unj´ı Aj` . t´ . B´ı ` A ´ Tones Recognition of YorUb 35 Table 3. Syllable statistics for the training set Tone Syllable types % of Total CV V Vn CVn N 59 (36%) 36 (22%) 29 (18%) 28 (17%) 12 (7%) 164 (46%) 20 (34%) 16 (27%) 8 (13%) 11 (19%) 4 (7%) 59 (17%) 43 (34%) 31 (25%) 22 (17%) 23 (18%) 8 (6%) 127 (36%) H M L Total 122 83 59 62 24 350 Table 4. Syllable statistics for the test set Tone Syllable types % of Total CV V Vn CVn N 18 (31%) 13 (22%) 10 (17%) 12 (21%) 5 (9%) 58 (46%) 10 (37%) 8 (30%) 2 (22%) 6 (22%) 1 (4%) 27 (22%) 14 (35%) 9 (22%) 5 (13%) 9 (22%) 3 (8%) 40 (32%) H M L Total 42 30 17 27 9 125 4 Raw speech 1 f0 profile extraction 2 3 f0 profile coding Reconised ANN model tone 8 ANN Weight Update 7 speech database 6 Desired output 5 Error computation Actual Output Fig.

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L. Burrows. Trainable Speech Synthesis. PhD thesis, Cambridge, Mar 1996. 10. Y. Cao, S. Zhang, T. Huang, and B. Xu. Tone modeling for continuous Mandarin speech recognition. International Journal of Speech Technology, 7:115–128, 2004. 11. P. C. Chang, S. W. Sue, and S. H. Chen. Mandarin tone recognition by multi-layer perceptron. In Proceedings on IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 517–520, 1990. 44 ` ad´ı O O unj´ı Aj` . t´ . B´ı 12. -H. -H. -R.

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