02193nas a2200301   4500000000100000000000100001008004100002260001200043653003300055653002100088653002300109653002700132653001900159653002400178653002100202100002700223700001700250700001600267700002300283700001700306700001700323245010500340856008100445300001200526490000600538520133300544022001401877       2022                            d  c06/202210aRestricted Boltzmann Machine10aSpectral Masking10aSpeech Enhancement10aSpeech Intelligibility10aSpeech Quality10aSupervised Learning10aMachine Learning1 aMuhammad Irfan Khattak1 aNasir Saleem1 aAamir Nawaz1 aAftab Ahmed Almani1 aFarhana Umer1 aElena Verdú00aERBM-SE: Extended Restricted Boltzmann Machine for Multi-Objective Single-Channel Speech Enhancement  uhttps://www.ijimai.org/journal/sites/default/files/2022-05/ijimai_7_4_16.pdf  a185-1950 v73 aMachine learning-based supervised single-channel speech enhancement has achieved considerable research interest over conventional approaches. In this paper, an extended Restricted Boltzmann Machine (RBM) is proposed for the spectral masking-based noisy speech enhancement. In conventional RBM, the acoustic features for the speech enhancement task are layerwise extracted and the feature compression may result in loss of vital information during the network training. In order to exploit the important information in the raw data, an extended RBM is proposed for the acoustic feature representation and speech enhancement. In the proposed RBM, the acoustic features are progressively extracted by multiple-stacked RBMs during the pre-training phase. The hidden acoustic features from the previous RBM are combined with the raw input data that serve as the new inputs to the present RBM. By adding the raw data to RBMs, the layer-wise features related to the raw data are progressively extracted, that is helpful to mine valuable information in the raw data. The results using the TIMIT database showed that the proposed method successfully attenuated the noise and gained improvements in the speech quality and intelligibility. The STOI, PESQ and SDR are improved by 16.86%, 25.01% and 3.84dB over the unprocessed noisy speech.  a1989-1660