Search Results for author: Kai Wei

Found 14 papers, 2 papers with code

Detect Profane Language in Streaming Services to Protect Young Audiences

no code implementations ACL (ECNLP) 2021 Jingxiang Chen, Kai Wei, Xiang Hao

With the rapid growth of online video streaming, recent years have seen increasing concerns about profane language in their content.

End-to-end spoken language understanding using joint CTC loss and self-supervised, pretrained acoustic encoders

no code implementations4 May 2023 Jixuan Wang, Martin Radfar, Kai Wei, Clement Chung

It is challenging to extract semantic meanings directly from audio signals in spoken language understanding (SLU), due to the lack of textual information.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +3

Dialog act guided contextual adapter for personalized speech recognition

no code implementations31 Mar 2023 Feng-Ju Chang, Thejaswi Muniyappa, Kanthashree Mysore Sathyendra, Kai Wei, Grant P. Strimel, Ross McGowan

Specifically, it leverages dialog acts to select the most relevant user catalogs and creates queries based on both -- the audio as well as the semantic relationship between the carrier phrase and user catalogs to better guide the contextual biasing.

Automatic Speech Recognition speech-recognition +1

2nd Place Solution to Google Landmark Retrieval 2020

no code implementations11 Jul 2022 Min Yang, Cheng Cui, Xuetong Xue, Hui Ren, Kai Wei

Using this method, we got a public score of 0. 40176 and a private score of 0. 36278 and achieved 2nd place in the Google Landmark Retrieval Competition 2020.


Multi-task RNN-T with Semantic Decoder for Streamable Spoken Language Understanding

no code implementations1 Apr 2022 Xuandi Fu, Feng-Ju Chang, Martin Radfar, Kai Wei, Jing Liu, Grant P. Strimel, Kanthashree Mysore Sathyendra

In addition, the NLU model in the two-stage system is not streamable, as it must wait for the audio segments to complete processing, which ultimately impacts the latency of the SLU system.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +4

Encoding Syntactic Knowledge in Transformer Encoder for Intent Detection and Slot Filling

no code implementations21 Dec 2020 Jixuan Wang, Kai Wei, Martin Radfar, Weiwei Zhang, Clement Chung

We propose a novel Transformer encoder-based architecture with syntactical knowledge encoded for intent detection and slot filling.

Intent Detection Multi-Task Learning +2

Jensen: An Easily-Extensible C++ Toolkit for Production-Level Machine Learning and Convex Optimization

2 code implementations17 Jul 2018 Rishabh Iyer, John T. Halloran, Kai Wei

This paper introduces Jensen, an easily extensible and scalable toolkit for production-level machine learning and convex optimization.

BIG-bench Machine Learning regression

Modeling and Simultaneously Removing Bias via Adversarial Neural Networks

no code implementations18 Apr 2018 John Moore, Joel Pfeiffer, Kai Wei, Rishabh Iyer, Denis Charles, Ran Gilad-Bachrach, Levi Boyles, Eren Manavoglu

In real world systems, the predictions of deployed Machine Learned models affect the training data available to build subsequent models.


Mixed Robust/Average Submodular Partitioning: Fast Algorithms, Guarantees, and Applications

no code implementations NeurIPS 2015 Kai Wei, Rishabh K. Iyer, Shengjie Wang, Wenruo Bai, Jeff A. Bilmes

In the present paper, we bridge this gap, by proposing several new algorithms (including greedy, majorization-minimization, minorization-maximization, and relaxation algorithms) that not only scale to large datasets but that also achieve theoretical approximation guarantees comparable to the state-of-the-art.

Clustering Distributed Optimization +3

Mixed Robust/Average Submodular Partitioning: Fast Algorithms, Guarantees, and Applications to Parallel Machine Learning and Multi-Label Image Segmentation

no code implementations NeurIPS 2015 Kai Wei, Rishabh Iyer, Shengjie Wang, Wenruo Bai, Jeff Bilmes

While the robust versions have been studied in the theory community, existing work has focused on tight approximation guarantees, and the resultant algorithms are not, in general, scalable to very large real-world applications.

Clustering Distributed Optimization +4

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