Search Results for author:
Found 10 papers, 4 papers with code
aoip.ai: An Open-Source P2P SDK
This white paper introduces aoip. ai, a groundbreaking open-source SDK incorporating peer-to-peer technology and advanced AI integration to transform VoIP and IoT applications.
Psychoacoustic Challenges Of Speech Enhancement On VoIP Platforms
Within the ambit of VoIP (Voice over Internet Protocol) telecommunications, the complexities introduced by acoustic transformations merit rigorous analysis.
LoFT: Local Proxy Fine-tuning For Improving Transferability Of Adversarial Attacks Against Large Language Model
We hypothesize that for attacks to be transferrable, it is sufficient if the proxy can approximate the target model in the neighborhood of the harmful query.
Improving Perceptual Quality, Intelligibility, and Acoustics on VoIP Platforms
In this paper, we present a method for fine-tuning models trained on the Deep Noise Suppression (DNS) 2020 Challenge to improve their performance on Voice over Internet Protocol (VoIP) applications.
TAPLoss: A Temporal Acoustic Parameter Loss for Speech Enhancement
We propose an objective for perceptual quality based on temporal acoustic parameters.
PAAPLoss: A Phonetic-Aligned Acoustic Parameter Loss for Speech Enhancement
We can add this criterion as an auxiliary loss to any model that produces speech, to optimize speech outputs to match the values of clean speech in these features.
Speech Enhancement for Virtual Meetings on Cellular Networks
We study speech enhancement using deep learning (DL) for virtual meetings on cellular devices, where transmitted speech has background noise and transmission loss that affects speech quality.
Cellular Network Speech Enhancement: Removing Background and Transmission Noise
The primary objective of speech enhancement is to reduce background noise while preserving the target's speech.
Improving Speech Enhancement through Fine-Grained Speech Characteristics
We first identify key acoustic parameters that have been found to correlate well with voice quality (e. g. jitter, shimmer, and spectral flux) and then propose objective functions which are aimed at reducing the difference between clean speech and enhanced speech with respect to these features.
Using Deep Learning Sequence Models to Identify SARS-CoV-2 Divergence
SARS-CoV-2 is an upper respiratory system RNA virus that has caused over 3 million deaths and infecting over 150 million worldwide as of May 2021.
