Auditory model-based estimation of the effect of head-worn devices on frontal horizontal localisation

Auditory localisation accuracy may be degraded when a head-worn device (HWD), such as a helmet or hearing protector, is used. A computational method is proposed in this study for estimating how horizontal plane localisation is impaired by a HWD through distortions of interaural cues. Head-related impulse responses (HRIRs) of different HWDs were measured with a KEMAR and a binaural auditory model was used to compute interaural cues from HRIR-convolved noise bursts. A shallow neural network (NN) was trained with data from a subjective listening experiment, where horizontal plane localisation was assessed while wearing different HWDs. Interaural cues were used as features to estimate perceived direction and position uncertainty (standard deviation) of a sound source in the horizontal plane with the NN. The NN predicted the position uncertainty of localisation among subjects for a given HWD with an average estimation error of 1°. The obtained results suggest that it is possible to predict the degradation of localisation ability for specific HWDs in the frontal horizontal plane using the method.

Bioinspired Auditory Model for Vowel Recognition

In this work, a bioinspired or neuromorphic model to replicate the vowel recognition process for an auditory system is presented. A bioinspired peripheral and central auditory system model is implemented and a neuromorphic higher auditory system model based on artificial neuronal nets for vowel recognition is proposed. For their verification, ten Hispanic Spanish language-speaking adults (five males and five females) were used. With the proposed bioinspired model based on artificial neuronal nets it is possible to recognize with high levels of accuracy and sensibility the vowels phonemes of speech signals and the assessment of cochlear implant stimulation strategies in terms of vowel recognition.

Speech intelligibility with various head-related transfer functions: A computational modeling approach

Speech intelligibility is known to be affected by the relative spatial position between target and interferers. The benefit of a spatial separation is, along with other factors, related to the head-related transfer function (HRTF). The HRTF is individually different and thus, the cues that improve speech intelligibility might also be different. In the current study an auditory model was employed to predict speech intelligibility with a variety of HRTFs. The predicted speech intelligibility was found to vary across HRTFs. Thus, individual listeners might have different access to cues that are important for speech intelligibility.

Assessing the perceived reverberation in different rooms for a set of musical instrument sounds

Previous research has shown that the perceived reverberation in a room, or reverberance, depends on the sound source that is being listened to. In a study by Osses et al. [(2017) J. Acoust. Soc. Am. 141(4), EL381-EL387], reverberance estimates obtained from an auditory model for 23 musical instrument sounds in 8 rooms supported this sound-source dependency. As a follow-up to that study, a listening experiment with 24 participants was conducted using a subset of the original sounds with the purpose of mapping each test sound onto a reverberance scale. The experimentally-obtained reverberance estimates were significantly correlated with the simulated reverberance, providing further evidence that the sensation of reverberance is sound-source dependent.