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Discriminative Training for Large-Vocabulary Speech Recognition Using Minimum Classification Error

IEEE transactions on audio, speech, and language processing, 2007, Vol.15 (1), p.203-223

2007

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End-to-End Multi-Speaker Speech Recognition

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018, p.4819-4823

2018

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SDR - Half-baked or Well Done?

ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019, p.626-630

2019

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Class-conditional Embeddings for Music Source Separation

ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019, p.301-305

2019

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Streaming Automatic Speech Recognition with the Transformer Model

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020, p.6074-6078

2020

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Alternative Objective Functions for Deep Clustering

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018, p.686-690

2018

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Triggered Attention for End-to-end Speech Recognition

ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019, p.5666-5670

2019

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An End-to-End Language-Tracking Speech Recognizer for Mixed-Language Speech

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018, p.4919-4923

2018

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Deep clustering: Discriminative embeddings for segmentation and separation

2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016, p.31-35

2016

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Deep clustering and conventional networks for music separation: Stronger together

2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2017-03, Vol.2017, p.61-65

2017

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End-To-End Multi-Speaker Speech Recognition With Transformer

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020, p.6134-6138

2020

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WHAMR!: Noisy and Reverberant Single-Channel Speech Separation

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020, p.696-700

2020

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The Phasebook: Building Complex Masks via Discrete Representations for Source Separation

ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019, p.66-70

2019

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MIMO-Speech: End-to-End Multi-Channel Multi-Speaker Speech Recognition

2019 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), 2019, p.237-244

2019

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Anomalous Sound Detection Using Attentive Neural Processes

2021 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), 2021, p.186-190

2021

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Phasebook and Friends: Leveraging Discrete Representations for Source Separation

IEEE journal of selected topics in signal processing, 2019-05, Vol.13 (2), p.370-382

2019

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The Sound Demixing Challenge 2023 – Cinematic Demixing Track

Transactions of the International Society for Music Information Retrieval, 2024-04, Vol.7 (1), p.44-62

2024

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On the Compensation Between Magnitude and Phase in Speech Separation

IEEE signal processing letters, 2021, Vol.28, p.2018-2022

2021

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Multi-Channel Deep Clustering: Discriminative Spectral and Spatial Embeddings for Speaker-Independent Speech Separation

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018, p.1-5

2018

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Phase-sensitive and recognition-boosted speech separation using deep recurrent neural networks

2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015, p.708-712

2015

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Semi-Supervised Speech Recognition Via Graph-Based Temporal Classification

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021, p.6548-6552

2021

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Momentum Pseudo-Labeling: Semi-Supervised ASR With Continuously Improving Pseudo-Labels

IEEE journal of selected topics in signal processing, 2022-10, Vol.16 (6), p.1424-1438

2022

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Cycle-consistency Training for End-to-end Speech Recognition

ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019, p.6271-6275

2019

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Unsupervised Speaker Adaptation Using Attention-Based Speaker Memory for End-to-End ASR

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020, p.7384-7388

2020

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Unsupervised Domain Adaptation for Speech Recognition via Uncertainty Driven Self-Training

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021, p.6553-6557

2021

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Discriminative Training for Large-Vocabulary Speech Recognition Using Minimum Classification Error

End-to-End Multi-Speaker Speech Recognition

SDR - Half-baked or Well Done?

Class-conditional Embeddings for Music Source Separation

Streaming Automatic Speech Recognition with the Transformer Model

Alternative Objective Functions for Deep Clustering

Triggered Attention for End-to-end Speech Recognition

An End-to-End Language-Tracking Speech Recognizer for Mixed-Language Speech

Deep clustering: Discriminative embeddings for segmentation and separation

Deep clustering and conventional networks for music separation: Stronger together

End-To-End Multi-Speaker Speech Recognition With Transformer

WHAMR!: Noisy and Reverberant Single-Channel Speech Separation

The Phasebook: Building Complex Masks via Discrete Representations for Source Separation

MIMO-Speech: End-to-End Multi-Channel Multi-Speaker Speech Recognition

Anomalous Sound Detection Using Attentive Neural Processes

Phasebook and Friends: Leveraging Discrete Representations for Source Separation

The Sound Demixing Challenge 2023 – Cinematic Demixing Track

On the Compensation Between Magnitude and Phase in Speech Separation

Multi-Channel Deep Clustering: Discriminative Spectral and Spatial Embeddings for Speaker-Independent Speech Separation

Phase-sensitive and recognition-boosted speech separation using deep recurrent neural networks

Semi-Supervised Speech Recognition Via Graph-Based Temporal Classification

Momentum Pseudo-Labeling: Semi-Supervised ASR With Continuously Improving Pseudo-Labels

Cycle-consistency Training for End-to-end Speech Recognition

Unsupervised Speaker Adaptation Using Attention-Based Speaker Memory for End-to-End ASR

Unsupervised Domain Adaptation for Speech Recognition via Uncertainty Driven Self-Training

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