Journal ArticleDOI
Nonintrusive Quality Assessment of Noise Suppressed Speech With Mel-Filtered Energies and Support Vector Regression
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TLDR
This paper proposes a nonintrusive metric for the quality assessment of noise-suppressed speech and utilizes the sensitivity of FBEs to noise in order to obtain an effective representation of speech towards quality assessment.Abstract:
Objective speech quality assessment is a challenging task which aims to emulate human judgment in the complex and time consuming task of subjective assessment. It is difficult to perform in line with the human perception due the complex and nonlinear nature of the human auditory system. The challenge lies in representing speech signals using appropriate features and subsequently mapping these features into a quality score. This paper proposes a nonintrusive metric for the quality assessment of noise-suppressed speech. The originality of the proposed approach lies primarily in the use of Mel filter bank energies (FBEs) as features and the use of support vector regression (SVR) for feature mapping. We utilize the sensitivity of FBEs to noise in order to obtain an effective representation of speech towards quality assessment. In addition, the use of SVR exploits the advantages of kernels which allow the regression algorithm to learn complex data patterns via nonlinear transformation for an effective and generalized mapping of features into the quality score. Extensive experiments conducted using two third party databases with different noise-suppressed speech signals show the effectiveness of the proposed approach.read more
Citations
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Journal ArticleDOI
Mulsemedia: State of the Art, Perspectives, and Challenges
TL;DR: A historic perspective on mulsemedia work is presented and current developments in the area are reviewed and standardization efforts, via the MPEG-V standard, are described.
Proceedings ArticleDOI
Quality-Net: An End-to-End Non-intrusive Speech Quality Assessment Model Based on BLSTM.
TL;DR: In this paper, an end-to-end, non-intrusive speech quality evaluation model, termed Quality-Net, based on bidirectional long short-term memory (LSTM) was proposed.
Posted Content
Quality-Net: An End-to-End Non-intrusive Speech Quality Assessment Model based on BLSTM
TL;DR: In this article, an end-to-end, non-intrusive speech quality evaluation model, termed Quality-Net, based on bidirectional long short-term memory (LSTM) was proposed.
Journal ArticleDOI
Long-Term Spectral Statistics for Voice Presentation Attack Detection
TL;DR: Investigations on ASVspoof 2015 challenge database and AVspoof database show that the proposed approach with a linear discriminative classifier yields a better system, irrespective of whether the spoofed signal is replayed to the microphone or is directly injected into the system software process.
Proceedings ArticleDOI
Novel deep autoencoder features for non-intrusive speech quality assessment
Meet H. Soni,Hemant A. Patil +1 more
TL;DR: Quantification of the experimental results suggests that proposed metric gives more accurate and correlated scores than an existing benchmark for objective, non-intrusive quality assessment metric ITU-T P.563 standard.
References
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Journal ArticleDOI
Robust Acoustic Speech Feature Prediction From Noisy Mel-Frequency Cepstral Coefficients
Ben Milner,Jonathan Darch +1 more
TL;DR: Noise compensation can be applied successfully to prediction with best performance given by a model adaptation method that performs only slightly worse than matched training and testing, and human listening tests show that the predicted features are sufficient for speech reconstruction and that noise compensation improves speech quality in noisy conditions.
Journal ArticleDOI
On the use of channel-attentive MFCC for robust recognition of partially corrupted speech
Hoon-Young Cho,Yung-Hwan Oh +1 more
TL;DR: Experimental results on the TIDIGITS database corrupted by various band-selective noises indicated that the proposed CAMFCC method utilizes the uncorrupted partial frequency bands better than a multiband method, resolving the limitation of noise localization caused by the fixed boundaries of the multiband approach.
Journal ArticleDOI
Two-scale Auditory Feature Based Non-intrusive Speech Quality Evaluation
Kartik Audhkhasi,Arun Kumar +1 more
TL;DR: A novel two-scale auditory feature based algorithm for non-intrusive evaluation of speech quality using the neuron firing probabilities along the length of the basilar membrane, from an explicit auditory model, to extract features from the distorted speech signal.
Journal ArticleDOI
Noise-Robust Speech Recognition Using Top-Down Selective Attention With an HMM Classifier
Changhoon Lee,Soo-Young Lee +1 more
TL;DR: For noise-robust speech recognition, a top-down attention mechanism was incorporated into a hidden Markov model classifier with Mel-frequency cepstral coefficient features and a low-complexity constraint was proposed to prevent the attention filter from over-fitting.
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