Noise robust algorithms to improve cell phone speech intelligibility for the hearing impaired - Ramani, Meena (ProQuest Dissertations & Theses, 2008)
Cell phone speech can lead to a difficult listening environment because of the environmental noise, the reduced bandwidth, the packet drop offs and the vocoder artifacts. This is especially true for hearing-impaired listeners who require a 9 dB improvement in signal to noise ratio (SNR) compared to normal-hearing listeners in order to understand speech in noise. This research explored various means to improve cell phone speech intelligibility for the hearing-impaired and resulted in the development of three novel hearing enhancement algorithms. The first algorithm developed by us is the recruitment based compensation (RBC) fitting method. RBC is a hearing enhancement algorithm aimed at improving speech intelligibility (SI) for unaided listeners with sensorineural hearing loss. It is a fitting algorithm which adjusts the gain parameters of the cell phone based on the individuals threshold of hearing. It provides multiple band gain and compression to make cell phone speech audible and within the reduced dynamic range of the hearing-impaired individual. Subjective hearing in noise tests (HINT) run on hearing-impaired subjects reveal that RBC shows a 15 dB improvement in SNR when compared to linear amplification which is typical of the cell phone volume control. RBC also shows a 6 dB improvement in SNR when compared to the desired sensation level (DSL) fitting method which is a popular audiology option. The second algorithm developed by us is the noise robust recruitment based compensation (NR-RBC) algorithm. NR-RBC is derived from RBC but uses the masked thresholds in noise instead of the thresholds in quiet. NR-RBC provides hearing loss compensation and automatic volume control in noisy environments. The objective speech intelligibility index (SII) scores indicate that NR-RBC has high speech usage when compared to all the other fitting methods. Both RBC and NR-RBC received a speech quality mean opinion score (MOS) of "Good." Though RBC and NR-RBC were designed with the hearing-impaired in mind the algorithm proves beneficial to the normal-hearing person with slight modifications. This resulted in a 3 dB improvement in SNR when compared to DSL using RBC, a 13 dB improvement in SNR using NR-RBC and a speech quality rating of "Good." For the aided hearing-impaired population, the hearing aid fitting acclimatization method was developed to improve speech intelligibility. Acclimatization occurs because of the plasticity of the auditory cortex. Acclimatization modeling was carried out using neural networks which were trained with multi-session Phonak hearing aid fitting data. This method is to be used in conjunction with existing hearing loss fitting algorithms and predicts the effect of hearing aid acclimatization. The mean square error (MSE) between the predicted values and the optimal values averaged across the parameters is lower than with the initial settings.