Non-negative matrix factorization (NMF) is a commonly used method for audio source separation in applications such as polyphonic music separation and noise removal. Previous research evaluated the use of additional algorithmic components and systems in efforts to improve the effectiveness of NMF. This study examined how the short-time Fourier transform (STFT) window duration used in the algorithm might affect detectable differences in separation performance. An ABX listening test compared speech extracted from two types of noise-contaminated mixtures at different window durations to determine if listeners could discriminate between them. It was found that the window duration had a significant impact on subject performance in both white- and conversation-noise cases with lower scores for the latter condition.
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