By Noam Shabtai

ISBN-10: 9533070978

ISBN-13: 9789533070971

**Read Online or Download Advances in Speech Recognition PDF**

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**Extra info for Advances in Speech Recognition **

**Example text**

By assuming that until the source was turned off it had been producing a stationary white noise, RT can be calculated from the RIR by using Schroeder’s energy decay curve [Schroeder, 1965] ∞ ∞ t 0 e (t ) = 10 log 10 ∫ h 2 (τ ) dτ − 10 log 10 ∫ h 2 (τ ) dτ (3) where h (t) is the RIR, and numerically solving e (RT) = −60dB. (4) In the ISO 3382 standard [ISO 3382:1997, 1997], RT is calculated from a least squares based linear fitting of Schroeder’s energy decay curve in order to compensate for the non-linearity and for the noise-floor effect.

J (1990), Finding structure in time, Cognitive Science, 14, pp. 179 – 211. Jordan, MI (1996), Neural networks, A Tucker editors, CRC handbook of computer science, CRC press. Bengio, Y (1996), Neural networks for speech and sequence recognition, Book published by International Thomson Computer Press. Looney, C G (1997), Pattern recognition using neural networks, theory and algorithms for engineers and scientists, book published by OUP USA. K. A Arbib Editors, The Handbook of Brain Theory and Neural Networks, MIT press.

CT−1. , c tn = c tn σn t = 0…T − 1 n = 1… N (8) where for every n = 1 . N, σn is the sample STD of the series cn0 . . cTn − 1 . 4. , 1996]. Speaker verification is the task of accepting or rejecting a tested speaker as a hypothetical speaker. Let X = [x0, x1, . . , xT−1] (9) be a segment of speech feature vectors xt of discrete time t ∈ {0, 1, . . , T − 1}. Let H1 represent the event that the tested speaker is the hypothetical speaker, and let H0 represent the opposite event. The model λ1 is defined to contain the parameters such that a parametric probability density function (PDF) p(X; λ1) would model the conditional PDF p(X|H1).

### Advances in Speech Recognition by Noam Shabtai

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