Binaural speech enhancement using a codebook based approach

2018 26th European Signal Processing Conference (EUSIPCO)

Nielsen

Christensen

et al. 2018

Self Cite

This paper deals with the estimation of the shortterm predictor (STP) parameters of speech and noise in a binaural framework. A binaural model based approach is proposed for estimating the power spectral density (PSD) of speech and noise at the individual ears for an arbitrary position of the speech source. The estimated PSDs can be subsequently used for enhancement in a binaural framework. The experimental results show that taking into account the position of the speech source using the proposed method leads to improved modelling and enhancement of the noisy speech. Index Terms-autoregressive modelling, binaural speech enhancement

Section: Motivationmentioning

confidence: 99%

Section: Model Based Estimation Of Stp Parametersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Model Based Estimation of STP Parameters for Binaural Speech Enhancement

2018 26th European Signal Processing Conference (EUSIPCO)

Nielsen

Christensen

et al. 2018

Self Cite

Model based binaural enhancement of voiced and unvoiced speech

2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Christensen

Boldt

2017

Self Cite

This paper deals with the enhancement of speech in presence of non-stationary babble noise. A binaural speech enhancement framework is proposed which takes into account both the voiced and unvoiced speech production model. The usage of this model in enhancement requires the Short term predictor (STP) parameters and the pitch information to be estimated. This paper uses a codebook based approach for estimating the STP parameters and a parametric binaural method is proposed for estimating the pitch parameters. Improvements in objective score are shown when using the voicedunvoiced speech model in comparison to the conventional unvoiced speech model.

Model-Based Speech Enhancement for Intelligibility Improvement in Binaural Hearing Aids

IEEE/ACM Trans. Audio Speech Lang. Process.

Nielsen

Boldt

et al. 2019

Self Cite

Speech intelligibility is often severely degraded among hearing impaired individuals in situations such as the cocktail party scenario. The performance of the current hearing aid technology has been observed to be limited in these scenarios. In this paper, we propose a binaural speech enhancement framework that takes into consideration the speech production model. The enhancement framework proposed here is based on the Kalman filter that allows us to take the speech production dynamics into account during the enhancement process. The usage of a Kalman filter requires the estimation of clean speech and noise short term predictor (STP) parameters, and the clean speech pitch parameters. In this work, a binaural codebookbased method is proposed for estimating the STP parameters, and a directional pitch estimator based on the harmonic model and maximum likelihood principle is used to estimate the pitch parameters. The proposed method for estimating the STP and pitch parameters jointly uses the information from left and right ears, leading to a more robust estimation of the filter parameters. Objective measures such as PESQ and STOI have been used to evaluate the enhancement framework in different acoustic scenarios representative of the cocktail party scenario. We have also conducted subjective listening tests on a set of nine normal hearing subjects, to evaluate the performance in terms of intelligibility and quality improvement. The listening tests show that the proposed algorithm, even with access to only a single channel noisy observation, significantly improves the overall speech quality, and the speech intelligibility by up to 15%.Index Terms-Kalman filter, binaural enhancement, pitch estimation, autoregressive model. 2329-9290 (c)