| 000 | 00917nam a22001577a 4500 | ||
|---|---|---|---|
| 999 |
_c19224 _d19224 |
||
| 020 | _a9783030914783 | ||
| 082 | _a006.454 MIT | ||
| 100 | _aMittag, Gabriel | ||
| 245 |
_aDeep learning based speech quality prediction / _cGabriel Mittag |
||
| 260 |
_aSwitzerland : _bSpringer, _c2022. |
||
| 300 | _a165 p. | ||
| 505 | _a1 Introduction 2 Quality Assessment of Transmitted Speech 3 Neural Network Architectures for Speech Quality Prediction 4 Double-Ended Speech Quality Prediction Using Siamese Networks 5 Prediction of Speech Quality Dimensions With Multi-Task Learning 6 Bias-Aware Loss for Training From Multiple Datasets 7 NISQA - A Single-Ended Speech Quality Model 8 Conclusions A Dataset Condition Tables B Train and Validation Dataset Dimension Histograms References | ||
| 650 | _aDeep learning | ||
| 650 | _aSpeech quality | ||
| 942 | _cRFT | ||