Dataset Groups Activity Stream WHAM! The WHAM! dataset is used for testing the proposed Bayesian factorised speaker-environment adaptive training and test time adaptation approach for Conformer models. BibTex: @dataset{G_Wichern_and_J_Antognini_and_M_Flynn_and_L_R_Zhu_and_E_McQuinn_and_D_Crow_and_E_Manilow_and_J_L_Roux_2024, abstract = {The WHAM! dataset is used for testing the proposed Bayesian factorised speaker-environment adaptive training and test time adaptation approach for Conformer models.}, author = {G. Wichern and J. Antognini and M. Flynn and L. R. Zhu and E. McQuinn and D. Crow and E. Manilow and J. L. Roux}, doi = {10.57702/q5tc6egb}, institution = {No Organization}, keyword = {'Deep Learning', 'Noise', 'Speech Recognition', 'Speech Separation', 'degraded utterances', 'noise reduction', 'noisy environments', 'speech processing', 'speech separation', 'voice conversion'}, month = {dec}, publisher = {TIB}, title = {WHAM!}, url = {https://service.tib.eu/ldmservice/dataset/wham-}, year = {2024} }
