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Low-latency Assistive Audio Enhancement for Neurodivergent People
Alexander Popescu, Rosie Frost, Milos Cernak
Neurodivergent people frequently experience decreased sound tolerance, with estimates suggesting it affects 50-70% of this population. This heightened sensitivity can provoke react…
DeepFilterGAN: A Full-band Real-time Speech Enhancement System with GAN-based Stochastic Regeneration
Sanberk Serbest, Tijana Stojkovic, Milos Cernak +1
In this work, we propose a full-band real-time speech enhancement system with GAN-based stochastic regeneration. Predictive models focus on estimating the mean of the target distri…
Cluster-based pruning techniques for audio data
Boris Bergsma, Marta Brzezinska, Oleg V. Yazyev +1
Deep learning models have become widely adopted in various domains, but their performance heavily relies on a vast amount of data. Datasets often contain a large number of irreleva…
In-Ear-Voice: Towards Milli-Watt Audio Enhancement With Bone-Conduction Microphones for In-Ear Sensing Platforms
Philipp Schilk, Niccolò Polvani, Andrea Ronco +2
The recent ubiquitous adoption of remote conferencing has been accompanied by omnipresent frustration with distorted or otherwise unclear voice communication. Audio enhancement can…
Speaker Embeddings as Individuality Proxy for Voice Stress Detection
Zihan Wu, Neil Scheidwasser-Clow, Karl El Hajal +1
Since the mental states of the speaker modulate speech, stress introduced by cognitive or physical loads could be detected in the voice. The existing voice stress detection benchma…
ALO-VC: Any-to-any Low-latency One-shot Voice Conversion
Bohan Wang, Damien Ronssin, Milos Cernak
This paper presents ALO-VC, a non-parallel low-latency one-shot phonetic posteriorgrams (PPGs) based voice conversion method. ALO-VC enables any-to-any voice conversion using only…