no code implementations • 1 Dec 2023 • Joseph Konan, Shikhar Agnihotri, Chia-Chun Hsieh
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.
no code implementations • 11 Oct 2023 • Joseph Konan, Ojas Bhargave, Shikhar Agnihotri, Shuo Han, Yunyang Zeng, Ankit Shah, Bhiksha Raj
Within the ambit of VoIP (Voice over Internet Protocol) telecommunications, the complexities introduced by acoustic transformations merit rigorous analysis.
no code implementations • 2 Oct 2023 • Muhammad Ahmed Shah, Roshan Sharma, Hira Dhamyal, Raphael Olivier, Ankit Shah, Joseph Konan, Dareen Alharthi, Hazim T Bukhari, Massa Baali, Soham Deshmukh, Michael Kuhlmann, Bhiksha Raj, Rita Singh
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.
no code implementations • 16 Mar 2023 • Joseph Konan, Ojas Bhargave, Shikhar Agnihotri, Hojeong Lee, Ankit Shah, Shuo Han, Yunyang Zeng, Amanda Shu, Haohui Liu, Xuankai Chang, Hamza Khalid, Minseon Gwak, Kawon Lee, Minjeong Kim, Bhiksha Raj
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.
2 code implementations • 16 Feb 2023 • Muqiao Yang, Joseph Konan, David Bick, Yunyang Zeng, Shuo Han, Anurag Kumar, Shinji Watanabe, Bhiksha Raj
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.
2 code implementations • 16 Feb 2023 • Yunyang Zeng, Joseph Konan, Shuo Han, David Bick, Muqiao Yang, Anurag Kumar, Shinji Watanabe, Bhiksha Raj
We propose an objective for perceptual quality based on temporal acoustic parameters.
1 code implementation • 2 Feb 2023 • Hojeong Lee, Minseon Gwak, Kawon Lee, Minjeong Kim, Joseph Konan, Ojas Bhargave
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.
no code implementations • 22 Jan 2023 • Amanda Shu, Hamza Khalid, Haohui Liu, Shikhar Agnihotri, Joseph Konan, Ojas Bhargave
The primary objective of speech enhancement is to reduce background noise while preserving the target's speech.
1 code implementation • 1 Jul 2022 • Muqiao Yang, Joseph Konan, David Bick, Anurag Kumar, Shinji Watanabe, Bhiksha Raj
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.
no code implementations • 12 Nov 2021 • Yanyi Ding, Zhiyi Kuang, Yuxin Pei, Jeff Tan, Ziyu Zhang, Joseph Konan
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.