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20192023
most citedOn End-to-end Multi-channel Time Domain Speech Separation in Reverberant Environments

49 citations · 86 across the 12 of their papers we have counts for

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10 papers · 1 filter

eess.AS2023★ 3 cited

A Teacher-Student approach for extracting informative speaker embeddings from speech mixtures

Tobias Cord-Landwehr, Christoph Boeddeker, Cătălin Zorilă +2

We introduce a monaural neural speaker embeddings extractor that computes an embedding for each speaker present in a speech mixture. To allow for supervised training, a teacher-stu…

eess.AS2023

Frame-wise and overlap-robust speaker embeddings for meeting diarization

Tobias Cord-Landwehr, Christoph Boeddeker, Cătălin Zorilă +2

Using a Teacher-Student training approach we developed a speaker embedding extraction system that outputs embeddings at frame rate. Given this high temporal resolution and the fact…

eess.AS2023

Self-regularised Minimum Latency Training for Streaming Transformer-based Speech Recognition

Mohan Li, Rama Doddipatla, Catalin Zorila

This paper proposes a self-regularised minimum latency training (SR-MLT) method for streaming Transformer-based automatic speech recognition (ASR) systems. In previous works, laten…

eess.AS2022★ 13 cited

Speaker Reinforcement Using Target Source Extraction for Robust Automatic Speech Recognition

Catalin Zorila, Rama Doddipatla

Improving the accuracy of single-channel automatic speech recognition (ASR) in noisy conditions is challenging. Strong speech enhancement front-ends are available, however, they ty…

eess.AS2022

Transformer-based Streaming ASR with Cumulative Attention

Mohan Li, Shucong Zhang, Catalin Zorila +1

In this paper, we propose an online attention mechanism, known as cumulative attention (CA), for streaming Transformer-based automatic speech recognition (ASR). Inspired by monoton…

eess.AS2021

Monaural source separation: From anechoic to reverberant environments

Tobias Cord-Landwehr, Christoph Boeddeker, Thilo von Neumann +3

Impressive progress in neural network-based single-channel speech source separation has been made in recent years. But those improvements have been mostly reported on anechoic data…

eess.AS2021★ 1 cited

Head-synchronous Decoding for Transformer-based Streaming ASR

Mohan Li, Catalin Zorila, Rama Doddipatla

Online Transformer-based automatic speech recognition (ASR) systems have been extensively studied due to the increasing demand for streaming applications. Recently proposed Decoder…

eess.AS2021★ 9 cited

Time-Domain Speech Extraction with Spatial Information and Multi Speaker Conditioning Mechanism

Jisi Zhang, Catalin Zorila, Rama Doddipatla +1

In this paper, we present a novel multi-channel speech extraction system to simultaneously extract multiple clean individual sources from a mixture in noisy and reverberant environ…

eess.AS2020★ 3 cited

Transformer-based Online Speech Recognition with Decoder-end Adaptive Computation Steps

Mohan Li, Catalin Zorila, Rama Doddipatla

Transformer-based end-to-end (E2E) automatic speech recognition (ASR) systems have recently gained wide popularity, and are shown to outperform E2E models based on recurrent struct…

eess.AS2020★ 49 cited

On End-to-end Multi-channel Time Domain Speech Separation in Reverberant Environments

Jisi Zhang, Catalin Zorila, Rama Doddipatla +1

This paper introduces a new method for multi-channel time domain speech separation in reverberant environments. A fully-convolutional neural network structure has been used to dire…