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

02/07/2021
by   Jisi Zhang, et al.
0

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 environments. The proposed method is built on an improved multi-channel time-domain speech separation network which employs speaker embeddings to identify and extract multiple targets without label permutation ambiguity. To efficiently inform the speaker information to the extraction model, we propose a new speaker conditioning mechanism by designing an additional speaker branch for receiving external speaker embeddings. Experiments on 2-channel WHAMR! data show that the proposed system improves by 9 baseline, and it increases the speech recognition accuracy by more than 16 relative over the same baseline.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/30/2021

Speaker conditioning of acoustic models using affine transformation for multi-speaker speech recognition

This study addresses the problem of single-channel Automatic Speech Reco...
research
10/12/2022

Individualized Conditioning and Negative Distances for Speaker Separation

Speaker separation aims to extract multiple voices from a mixed signal. ...
research
03/15/2023

Beamformer-Guided Target Speaker Extraction

We propose a Beamformer-guided Target Speaker Extraction (BG-TSE) method...
research
10/28/2022

Local-global speaker representation for target speaker extraction

Target speaker extraction is to extract the target speaker's voice from ...
research
10/20/2021

Time-Domain Mapping Based Single-Channel Speech Separation With Hierarchical Constraint Training

Single-channel speech separation is required for multi-speaker speech re...
research
03/31/2022

A Hybrid Continuity Loss to Reduce Over-Suppression for Time-domain Target Speaker Extraction

Speaker extraction algorithm extracts the target speech from a mixture s...
research
04/15/2022

Speaker-Aware Mixture of Mixtures Training for Weakly Supervised Speaker Extraction

Dominant researches adopt supervised training for speaker extraction, wh...

Please sign up or login with your details

Forgot password? Click here to reset