Skip to search formSkip to main contentSkip to account menu
On Training Targets for Supervised Speech Separation
TLDR
Results in various test conditions reveal that the two ratio mask targets, the IRM and the FFT-MASK, outperform the other targets in terms of objective intelligibility and quality metrics, and that masking based targets, in general, are significantly better than spectral envelope based targets.
View on ACM
On Ideal Binary Mask As the Computational Goal of Auditory Scene Analysis
  • Deliang Wang
  • Psychology
    Speech Separation by Humans and Machines
  • 2005
TLDR
This chapter is an attempt at a computational-theory analysis of auditory scene analysis, where the main task is to understand the character of the CASA problem.
View via Publisher
Monaural speech segregation based on pitch tracking and amplitude modulation
TLDR
This work proposes a novel system for voiced speech segregation that segregates resolved and unresolved harmonics differently, and it yields substantially better performance, especially for the high-frequency part of speech.
View on IEEE
Supervised Speech Separation Based on Deep Learning: An Overview
TLDR
This paper provides a comprehensive overview of the research on deep learning based supervised speech separation in the last several years, and provides a historical perspective on how advances are made.
View on ACM
Complex Ratio Masking for Monaural Speech Separation
TLDR
The proposed approach improves over other methods when evaluated with several objective metrics, including the perceptual evaluation of speech quality (PESQ), and a listening test where subjects prefer the proposed approach with at least a 69% rate.
View on ACM
A multipitch tracking algorithm for noisy speech
TLDR
This work presents a robust algorithm for multipitch tracking of noisy speech that combines an improved channel and peak selection method, a new method for extracting periodicity information across different channels, and a hidden Markov model for forming continuous pitch tracks.
View via Publisher
Image Segmentation Based on Oscillatory Correlation
TLDR
It is argued that LEGION provides a novel and effective framework for image segmentation and figure-ground segregation and exhibits a natural capacity in segmenting images.
View on MIT Press
Ideal ratio mask estimation using deep neural networks for robust speech recognition
TLDR
The proposed feature enhancement algorithm estimates a smoothed ideal ratio mask (IRM) in the Mel frequency domain using deep neural networks and a set of time-frequency unit level features that has previously been used to estimate the ideal binary mask.
View on IEEE
Separation of speech from interfering sounds based on oscillatory correlation
TLDR
A multistage neural model is proposed for an auditory scene analysis task--segregating speech from interfering sound sources, a two-layer oscillator network that performs stream segregation on the basis of oscillatory correlation.
View on PubMed
A two-stage algorithm for one-microphone reverberant speech enhancement
TLDR
A comparison with a recent enhancement algorithm is made on a corpus of speech utterances in a number of reverberant conditions, and the results show that the proposed algorithm performs substantially better.
View on IEEE
...
...
By clicking accept or continuing to use the site, you agree to the terms outlined in our Privacy Policy, Terms of Service, and Dataset License