Noisy speech enhancement based on long term harmonic model to improve speech intelligibility for hearing impaired listeners

This study proposes a speech enhancement algorithm to improve speech intelligibility for hearing impaired listeners in adverse conditions. The proposed algorithm is based on a long term harmonic model, where the harmonics of target speech are more distinguished from noise spectrum interference. Our method consists of two stages: i) Prominent pitch estimation based on long term harmonic feature analysis and neural network classification. ii) Target speech spectrum estimation with pitch information based on long term noise spectrum extraction. The listening experiment with EAS vocoder speech shows that our algorithm is substantially beneficial for cochlear implant recipients to perceive speech in noisy environment in terms of word recognition rate.