Sentence examples for unprocessed speech from inspiring English sources

Both of the methods were rated lower in quality than unprocessed speech in clean conditions.

The performance of the proposed methods was evaluated by first comparing them to unprocessed speech using objective quality measures as well as subjective loudness and listening preference tests.

The clean speech signal is estimated by a convex combination of the unprocessed speech signal and the output of a linear predictor.

Both of the methods were able to increase loudness in some bandwidth conditions as well as outperform unprocessed speech and dynamic range compression in terms of intelligibility in high-noise levels.

Based on the results of these evaluations, the phase-modification methods were further compared to unprocessed speech and dynamic range compression using subjective word-error rate and quality tests.

In background noise, however, where intelligibility enhancement algorithms are mostly used, both methods achieved similar results to unprocessed speech in terms of listening preference in some of the bandwidth conditions tested.

"Rev" represents unprocessed reverberant speech.

Clearly, RTA-DNNSpatial yielded higher fwSegSNR scores than the unprocessed reverberant speech and WPE at each RT60s.

As shown in Fig. 13, compared with unprocessed reverberant speech, WPE, DSB-DNN, and DNNs-DSB, the nonoracle case substantially boosted fwSegSNR scores at all RT60s.

Figure 6 illustrated that when compared to unprocessed reverberant speech, our proposed DNN-baseline could achieve a significant fwSegSNR improvement of 3.5 dB on the average at all RT60s, including mismatched conditions of RIRs and unseen speakers.

This is because that the kurtosis of some unprocessed signals such as speech signals is also high, but we do not perceive speech as musical noise.