no code implementations • 1 Feb 2024 • Masahito Togami, Jean-Marc Valin, Karim Helwani, Ritwik Giri, Umut Isik, Michael M. Goodwin
The algorithm runs in real-time on 10-ms frames with a 40 ms of look-ahead.
no code implementations • 23 Feb 2023 • Zhepei Wang, Ritwik Giri, Devansh Shah, Jean-Marc Valin, Michael M. Goodwin, Paris Smaragdis
In this study, we present an approach to train a single speech enhancement network that can perform both personalized and non-personalized speech enhancement.
no code implementations • 18 Jun 2022 • Zhepei Wang, Ritwik Giri, Shrikant Venkataramani, Umut Isik, Jean-Marc Valin, Paris Smaragdis, Mike Goodwin, Arvindh Krishnaswamy
In this work, we propose Exformer, a time-domain architecture for target speaker extraction.
no code implementations • 16 Jun 2022 • Jean-Marc Valin, Ritwik Giri, Shrikant Venkataramani, Umut Isik, Arvindh Krishnaswamy
In real life, room effect, also known as room reverberation, and the present background noise degrade the quality of speech.
no code implementations • 28 Mar 2022 • Siyuan Yuan, Zhepei Wang, Umut Isik, Ritwik Giri, Jean-Marc Valin, Michael M. Goodwin, Arvindh Krishnaswamy
Singing voice separation aims to separate music into vocals and accompaniment components.
no code implementations • 8 Jun 2021 • Ritwik Giri, Shrikant Venkataramani, Jean-Marc Valin, Umut Isik, Arvindh Krishnaswamy
The presence of multiple talkers in the surrounding environment poses a difficult challenge for real-time speech communication systems considering the constraints on network size and complexity.
no code implementations • 16 Feb 2021 • Zhepei Wang, Ritwik Giri, Umut Isik, Jean-Marc Valin, Arvindh Krishnaswamy
Given a limited set of labeled data, we present a method to leverage a large volume of unlabeled data to improve the model's performance.
no code implementations • 12 Feb 2021 • Jonah Casebeer, Vinjai Vale, Umut Isik, Jean-Marc Valin, Ritwik Giri, Arvindh Krishnaswamy
Audio codecs based on discretized neural autoencoders have recently been developed and shown to provide significantly higher compression levels for comparable quality speech output.
no code implementations • 11 Aug 2020 • Umut Isik, Ritwik Giri, Neerad Phansalkar, Jean-Marc Valin, Karim Helwani, Arvindh Krishnaswamy
Neural network applications generally benefit from larger-sized models, but for current speech enhancement models, larger scale networks often suffer from decreased robustness to the variety of real-world use cases beyond what is encountered in training data.
1 code implementation • 30 Jan 2020 • Bahareh Tolooshams, Ritwik Giri, Andrew H. Song, Umut Isik, Arvindh Krishnaswamy
Supervised deep learning has gained significant attention for speech enhancement recently.
Ranked #2 on Speech Enhancement on CHiME-3
no code implementations • WS 2020 • Marcello Federico, Robert Enyedi, Roberto Barra-Chicote, Ritwik Giri, Umut Isik, Arvindh Krishnaswamy, Hassan Sawaf
We present enhancements to a speech-to-speech translation pipeline in order to perform automatic dubbing.
no code implementations • 30 Mar 2017 • Igor Fedorov, Ritwik Giri, Bhaskar D. Rao, Truong Q. Nguyen
We propose a novel method called the Relevance Subject Machine (RSM) to solve the person re-identification (re-id) problem.
no code implementations • 6 May 2016 • Igor Fedorov, Ritwik Giri, Bhaskar D. Rao, Truong Q. Nguyen
In this paper, we present a novel Bayesian approach to recover simultaneously block sparse signals in the presence of outliers.
no code implementations • 7 Apr 2016 • Igor Fedorov, Alican Nalci, Ritwik Giri, Bhaskar D. Rao, Truong Q. Nguyen, Harinath Garudadri
We show that the proposed framework encompasses a large class of S-NNLS algorithms and provide a computationally efficient inference procedure based on multiplicative update rules.
no code implementations • 17 Jul 2015 • Ritwik Giri, Bhaskar D. Rao
In this paper, we propose a generalized scale mixture family of distributions, namely the Power Exponential Scale Mixture (PESM) family, to model the sparsity inducing priors currently in use for sparse signal recovery (SSR).