Speaker Separation
11 papers with code • 0 benchmarks • 3 datasets
Benchmarks
These leaderboards are used to track progress in Speaker Separation
LibriCSS
FSDnoisy18k
Latest papers with no code
New Insights on Target Speaker Extraction
However, such studies have been conducted on a few datasets and have not considered recent deep neural network architectures for SS that have shown impressive separation performance.
Location-based training for multi-channel talker-independent speaker separation
We further demonstrate the effectiveness of LBT for the separation of four and five concurrent speakers.
Online Self-Attentive Gated RNNs for Real-Time Speaker Separation
Our stateful implementation for online separation leads to a minor drop in performance compared to the offline model; 0. 8dB for monaural inputs and 0. 3dB for binaural inputs while reaching a real-time factor of 0. 65.
Personalized Keyphrase Detection using Speaker and Environment Information
In this paper, we introduce a streaming keyphrase detection system that can be easily customized to accurately detect any phrase composed of words from a large vocabulary.
Guided Training: A Simple Method for Single-channel Speaker Separation
Another way is to use an anchor speech, a short speech of the target speaker, to model the speaker identity.
On permutation invariant training for speech source separation
We study permutation invariant training (PIT), which targets at the permutation ambiguity problem for speaker independent source separation models.
High Fidelity Speech Regeneration with Application to Speech Enhancement
Speech enhancement has seen great improvement in recent years mainly through contributions in denoising, speaker separation, and dereverberation methods that mostly deal with environmental effects on vocal audio.
Interactive Speech and Noise Modeling for Speech Enhancement
In this paper, we propose a novel idea to model speech and noise simultaneously in a two-branch convolutional neural network, namely SN-Net.
Informed Source Extraction With Application to Acoustic Echo Reduction
Recent deep learning-based methods leverage a speaker discriminative model that maps a reference snippet uttered by the target speaker into a single embedding vector that encapsulates the characteristics of the target speaker.
Speaker Separation Using Speaker Inventories and Estimated Speech
We propose speaker separation using speaker inventories and estimated speech (SSUSIES), a framework leveraging speaker profiles and estimated speech for speaker separation.
