• Corpus ID: 18328317

# Joint Estimation of Reverberation Time and Direct-to-Reverberation Ratio from Speech using Auditory-Inspired Features

@article{Xiong2015JointEO,
title={Joint Estimation of Reverberation Time and Direct-to-Reverberation Ratio from Speech using Auditory-Inspired Features},
author={Feifei Xiong and Stefan Goetze and Bernd T. Meyer},
journal={ArXiv},
year={2015},
volume={abs/1510.04620}
}
• Published 15 October 2015
• Computer Science
• ArXiv
Blind estimation of acoustic room parameters such as the reverberation time $T_\mathrm{60}$ and the direct-to-reverberation ratio ($\mathrm{DRR}$) is still a challenging task, especially in case of blind estimation from reverberant speech signals. In this work, a novel approach is proposed for joint estimation of $T_\mathrm{60}$ and $\mathrm{DRR}$ from wideband speech in noisy conditions. 2D Gabor filters arranged in a filterbank are exploited for extracting features, which are then used as…
17 Citations

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## References

SHOWING 1-10 OF 42 REFERENCES
Noise-robust reverberation time estimation using spectral decay distributions with reduced computational cost
• Physics
2013 IEEE International Conference on Acoustics, Speech and Signal Processing
• 2013
A novel T60 estimation algorithm based on spectral decay distributions that provides robustness to additive noise for a range of realistic noise types for signal-to-noise ratios in the range 0 to 35 dB and T60s between 200 and 950 ms is described.
Temporal Dynamics for Blind Measurement of Room Acoustical Parameters
• Physics
IEEE Transactions on Instrumentation and Measurement
• 2010
Experiments suggest that estimators of subjective perception of spectral coloration, reverberant tail effect, and overall speech quality can be obtained with an adaptive speech-to-reverberation modulation energy ratio measure.
Blind estimation of reverberation time.
• Physics
The Journal of the Acoustical Society of America
• 2003
A method for estimating RT without prior knowledge of sound sources or room geometry is presented, and results obtained for simulated and real room data are in good agreement with the real RT values.
Monaural room acoustic parameters from music and speech.
• Physics
The Journal of the Acoustical Society of America
• 2008
An approach which uses statistical machine learning, previously developed for speech, is extended to work with music to estimate parameters relating to the balance of early and late energies in the impulse response.
Blind estimation of reverberation time based on the distribution of signal decay rates
• Physics
2008 IEEE International Conference on Acoustics, Speech and Signal Processing
• 2008
A method to estimate the reverberation time using a property of the distribution of the decay rates in the short-time Fourier transform domain and results using simulated and real reverberant speech signals are demonstrated.
Direct-to-Reverberant Ratio estimation using a null-steered beamformer
• Physics
2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
• 2015
A novel DRR estimation algorithm applicable where the signal was recorded with two or more microphones, such as mobile communications devices and laptops is described, which yields accurate DRR estimates to within ±4 dB across a wide variety of room sizes, reverberation times and source-receiver distances.
Extracting Room Reverberation Time from Speech Using Artificial Neural Networks
• Physics
• 2001
A novel method to extract the reverberation time from reverberated speech utterances is presented. In this study, speech utterances are restricted to pronounced digits; uncontrolled discourse is not
Single-Microphone LP Residual Skewness-Based Inverse Filtering of the Room Impulse Response
• Engineering
IEEE Transactions on Audio, Speech, and Language Processing
• 2012
The proposed method is shown to be superior to the method by Wu and Wang, particularly in terms of reducing the coloration effect, and the effectiveness of the proposed method for time delay estimation (TDE).
Blind estimation of reverberation time based on spectro-temporal modulation filtering
• Computer Science
2013 IEEE International Conference on Acoustics, Speech and Signal Processing
• 2013
A novel method for blind estimation of the reverberation time (RT60) is proposed based on applying spectro-temporal modulation filters to time-frequency representations. 2D-Gabor filters arranged in
An Improved Algorithm for Blind Reverberation Time Estimation
• Physics
• 2010
An improved algorithm for the estimation of the reverberation time (RT) from reverberant speech signals is presented, based on a simple statistical model for the sound decay such that the RT can be estimated by means of a maximum-likelihood (ML) estimator.