Deafness-in-a-dish: modeling hereditary deafness with inner ear organoids

Sensorineural hearing loss (SNHL) is a major cause of functional disability in both the developed and developing world. While hearing aids and cochlear implants provide significant benefit to many with SNHL, neither targets the cellular and molecular dysfunction that ultimately underlies SNHL. The successful development of more targeted approaches, such as growth factor, stem cell, and gene therapies, will require a yet deeper understanding of the underlying molecular mechanisms of human hearing and deafness. Unfortunately, the human inner ear cannot be biopsied without causing significant, irreversible damage to the hearing or balance organ. Thus, much of our current understanding of the cellular and molecular biology of human deafness, and of the human auditory system more broadly, has been inferred from observational and experimental studies in animal models, each of which has its own advantages and limitations. In 2013, researchers described a protocol for the generation of inner ear organoids from pluripotent stem cells (PSCs), which could serve as scalable, high-fidelity alternatives to animal models. Here, we discuss the advantages and limitations of conventional models of the human auditory system, describe the generation and characteristics of PSC-derived inner ear organoids, and discuss several strategies and recent attempts to model hereditary deafness in vitro. Finally, we suggest and discuss several focus areas for the further, intensive characterization of inner ear organoids and discuss the translational applications of these novel models of the human inner ear.

Speech enhancement based on perceptually motivated guided spectrogram filtering

In this paper, a single-channel speech enhancement algorithm is proposed by using guided spectrogram filtering based on masking properties of human auditory system when considering a speech spectrogram as an image. Guided filtering is capable of sharpening details and estimating unwanted textures or background noise from the noisy speech spectrogram. If we consider the noisy spectrogram as a degraded image, we can estimate the spectrogram of the clean speech signal using guided filtering after subtracting noise components. Combined with masking properties of human auditory system, the proposed algorithm adaptively adjusts and reduces the residual noise of the enhanced speech spectrogram according to the corresponding masking threshold. Because the filtering output is a local linear transform of the guidance spectrogram, the local mask window slides can be efficiently implemented via box filter with O(N) computational complexity. Experimental results show that the proposed algorithm can effectively suppress noise in different noisy environments and thus can greatly improve speech quality and speech intelligibility.

Audio Watermarking Schemes: A Comparative Analysis

The growth of internet and its reachability to all sectors of people have never been greater. Internet has become the best marketplace, the best library and may be the best guide for everything. But this revolution comes with some bigger problems. One of the most challenging problems among them would be copyright protection of digital data being transferred over internet. Digital images, videos and audios undergo illegal re-production and re-distributions, tampering and other acts of copyright violation. This is proved to have leading the film and other prominent industries to loss of millions of dollars per year. Encrypting the data provides security to it. In this case only people who pay to buy the secret key that should be used for decryption can use the data. But the problem is that once decrypted, the data can be re-produced into any number of copies and can be re-distributed without any permission from the author. Watermarking is an intelligent solution for this problem where the presence of watermark can be checked to distinguish pirated copies from the actual ones. A lot of methods have been developed for image and video watermarking, but the research on audio watermarking started a little bit later. The reason might be the fact that audio watermarking is tedious compared to image and video as Human Auditory System (HAS) is more sensitive compared to Human Visionary System. So ensuring the imperceptibility of audio watermarks is a tougher task. In this thesis various audio watermarking schemes introduced so far in the literature and their merits and demerits are studied.