AES Journal Forum

Confidence Measures for Nonintrusive Estimation of Speech Clarity Index

Document Thumbnail

In many situations, measuring the amount and type of reverberation in a room assumes that the room impulse response is available for the computation. When that impulse response is not available, a nonintrusive room acoustic (NIRA) method must be used. In this report, the authors use the C50 clarity index to characterize reverberation in the signal because it has been shown to be more highly correlated with the speech recognition performance then other measures of reverberation. Multiple features are extracted from a reverberant speech signal and they are then used to train a bidirectional long short-term memory model that maps from the feature space into the target C50 value. Prediction intervals, which provide an upper and lower bound of the estimate, can be derived from the standard deviation of the per frame estimations. Confidence measures are then obtained by normalizing these prediction intervals. These measures are highly correlated with the absolute C50 estimation errors. The performance of the prediction intervals and confidence measure are shown to be consistent in many different noisy reverberant environments. The procedure proposed in this paper for deriving C50 prediction intervals and confidence measures could as well be applied to other room acoustic parameter estimation, for example, T60 (reverberation decay time to 60 dB) or DRR (direct to reverberation ratio).

JAES Volume 65 Issue 1/2 pp. 90-99; January 2017
Publication Date:

Click to purchase paper as a non-member or you can login as an AES member to see more options.

No AES members have commented on this paper yet.

Subscribe to this discussion

RSS Feed To be notified of new comments on this paper you can subscribe to this RSS feed. Forum users should login to see additional options.

Start a discussion!

If you would like to start a discussion about this paper and are an AES member then you can login here:

If you are not yet an AES member and have something important to say about this paper then we urge you to join the AES today and make your voice heard. You can join online today by clicking here.

AES - Audio Engineering Society