Search Results for author: Vahid Noroozi

Found 12 papers, 3 papers with code

NVIDIA NeMo Offline Speech Translation Systems for IWSLT 2022

no code implementations IWSLT (ACL) 2022 Oleksii Hrinchuk, Vahid Noroozi, Ashwinkumar Ganesan, Sarah Campbell, Sandeep Subramanian, Somshubra Majumdar, Oleksii Kuchaiev

Our cascade system consists of 1) Conformer RNN-T automatic speech recognition model, 2) punctuation-capitalization model based on pre-trained T5 encoder, 3) ensemble of Transformer neural machine translation models fine-tuned on TED talks.

Automatic Speech Recognition Machine Translation +3

SGD-QA: Fast Schema-Guided Dialogue State Tracking for Unseen Services

no code implementations17 May 2021 Yang Zhang, Vahid Noroozi, Evelina Bakhturina, Boris Ginsburg

In this paper, we propose SGD-QA, a simple and extensible model for schema-guided dialogue state tracking based on a question answering approach.

Dialogue State Tracking Goal-Oriented Dialogue Systems +1

SPGISpeech: 5,000 hours of transcribed financial audio for fully formatted end-to-end speech recognition

1 code implementation5 Apr 2021 Patrick K. O'Neill, Vitaly Lavrukhin, Somshubra Majumdar, Vahid Noroozi, Yuekai Zhang, Oleksii Kuchaiev, Jagadeesh Balam, Yuliya Dovzhenko, Keenan Freyberg, Michael D. Shulman, Boris Ginsburg, Shinji Watanabe, Georg Kucsko

In the English speech-to-text (STT) machine learning task, acoustic models are conventionally trained on uncased Latin characters, and any necessary orthography (such as capitalization, punctuation, and denormalization of non-standard words) is imputed by separate post-processing models.

speech-recognition Speech Recognition

I-ODA, Real-World Multi-modal Longitudinal Data for OphthalmicApplications

no code implementations30 Mar 2021 Nooshin Mojab, Vahid Noroozi, Abdullah Aleem, Manoj P. Nallabothula, Joseph Baker, Dimitri T. Azar, Mark Rosenblatt, RV Paul Chan, Darvin Yi, Philip S. Yu, Joelle A. Hallak

In this paper, we present a new multi-modal longitudinal ophthalmic imaging dataset, the Illinois Ophthalmic Database Atlas (I-ODA), with the goal of advancing state-of-the-art computer vision applications in ophthalmology, and improving upon the translatable capacity of AI based applications across different clinical settings.

Semi-supervised Deep Representation Learning for Multi-View Problems

no code implementations11 Nov 2018 Vahid Noroozi, Sara Bahaadini, Lei Zheng, Sihong Xie, Weixiang Shao, Philip S. Yu

While neural networks for learning representation of multi-view data have been previously proposed as one of the state-of-the-art multi-view dimension reduction techniques, how to make the representation discriminative with only a small amount of labeled data is not well-studied.

Dimensionality Reduction Learning Representation Of Multi-View Data

DIRECT: Deep Discriminative Embedding for Clustering of LIGO Data

no code implementations7 May 2018 Sara Bahaadini, Vahid Noroozi, Neda Rohani, Scott Coughlin, Michael Zevin, Aggelos K. Katsaggelos

In this paper, benefiting from the strong ability of deep neural network in estimating non-linear functions, we propose a discriminative embedding function to be used as a feature extractor for clustering tasks.

Joint Deep Modeling of Users and Items Using Reviews for Recommendation

5 code implementations17 Jan 2017 Lei Zheng, Vahid Noroozi, Philip S. Yu

One of the networks focuses on learning user behaviors exploiting reviews written by the user, and the other one learns item properties from the reviews written for the item.

Recommendation Systems

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