Presentation of the studied cases Clauses Exemplaires

Presentation of the studied cases. The performance of wavelets thresholding methods presented (see Section 2.2) is studied for experimental signals formed by speech signals and industrial noises. The quality of the denois- ing obtained is quantified using four selection criteria. A database of 42 508 800 values of the different criteria is generated, its composition is given in Table 2.1. Firstly, the experimental signals used in simulations are presented (see Section 2.3.1): 8 200 signals are tested. Sec- ondly, the parameters of wavelet denoising methods tested are exposed in details (see Section 2.3.2): 1 296 denoising methods are tested. Thirdly, the four selection criteria used to quantify the quality of the denoising achieved are explained (see Section 2.3.3). The twenty speech signals used come from the TIMIT database (Xxxxxxxx et al., 1993). Ten English phrases spoken by a woman and the same ten phrases spoken by a man were selected. For this study, an industrial noise is considered to be any noise to which a worker is exposed in an industrial workplace. Ten industrial noises are used. Two are extracted from the NOISEX database (NOISEX , 1990), they are recorded in a car factory. The eight others are recorded in different locations at the NORANDA CCR copper refinery in Montreal (J. Voix, personal communication, 2000).The ten industrial noises tested could almost be considered as stationary since their frequency components vary only slightly over time. In addition to these recorded noises, white and pink Gaussian noises are tested to compare their behaviour to the industrial noises one and to identify which one of the two best simulates industrial noises in a speech denoising treatment. Thus, two hundred (20 × 10) speech-noise pairs are formed. Every noised speech signal x is obtained by adding an industrial noise w to a speech signal s according to Eq. (2.21). std(s) 10SNR /20 + w std(w) with std(s) =