Also, it has already been proposed that spontaneous random activity, i.e. Especially in neuroscience, it has been demonstrated to play an essential role in a vast number of different systems. SR occurs ubiquitously in nature and covers a broad spectrum of systems in physical and biological contexts. , refers to a processing principle in which signals that would otherwise be sub-threshold for a given sensor can be detected by adding a random signal of appropriate intensity to the sensor input. The term stochastic resonance (SR), first introduced by Benzi et al. However, a vast and still increasing number of publications demonstrate the various benefits of noise for signal detection and processing, among which the most important phenomena are called stochastic resonance, coherence resonance, and recurrence resonance. The term noise usually describes undesirable disturbances or fluctuations, and is considered to be the “fundamental enemy” for communication and error-free information transmission and processing in engineering. This surprising result indicates that intrinsic noise might not only play a crucial role in human auditory processing, but might even be beneficial for contemporary machine learning approaches. Remarkably, speech recognition after hearing loss actually improves with additional intrinsic noise. We simulate different levels of hearing loss and investigate the effect of intrinsic noise. Here we present a computational model of the auditory pathway based on a deep neural network, trained on speech recognition. Especially within the auditory system, recent studies suggest that intrinsic noise plays a key role in signal processing and might even correspond to increased spontaneous neuronal firing rates observed in early processing stages of the auditory brain stem and cortex after hearing loss. However, in the context of stochastic resonance, noise has been shown to improve signal detection of weak subthreshold signals, and it has been proposed that the brain might actively exploit this phenomenon. Noise is generally considered to harm information processing performance.
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