Nonnegative matrix factorization-based frequency lowering technology for Mandarin-speaking hearing aid users

摘要

Frequency lowering technologies have demonstrated effectiveness in English speech recognition for English-speaking people with high-frequency hearing loss. Their effect on Mandarin speech has not been well investigated. This paper serves two important purposes: it 1) examines the effect of frequency transposition (FT), a category of frequency lowering technologies, on Mandarin speech recognition, and 2) proposes a dictionary-based FT framework based on nonnegative matrix factorization (NMF) that is transferable across languages. Our results show that the proposed NMF-FT improves Mandarin consonant identification as compared to the traditional FT, with particularly significant improvements in affricates and fricatives.