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Semantic Labeling of Quality Impairments in Speech Spectrograms with Deep Convolutional Networks.

, and . QoMEX, page 1-3. IEEE, (2019)

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Removing the Bias in Speech Quality Scores Collected in Noisy Crowdsourcing Environments., , and . QoMEX, page 49-54. IEEE, (2021)Diagnostic and Summative Approach for Predicting Speech Communication Quality in a Super-Wideband Context., , , and . ITG Symposium on Speech Communication, page 1-5. VDE / IEEE, (2018)Machine learning based speech quality prediction.. Technical University of Berlin, Germany, (2022)Semantic Labeling of Quality Impairments in Speech Spectrograms with Deep Convolutional Networks., and . QoMEX, page 1-3. IEEE, (2019)Extending the E-Model Towards Super-Wideband and Fullband Speech Communication Scenarios., , , , and . INTERSPEECH, page 3436-3440. ISCA, (2019)Variable Voice Likability Affecting Subjective Speech Quality Assessments., , , and . QoMEX, page 1-6. IEEE, (2018)Quality Estimation of Noisy Speech Using Spectral Entropy Distance., and . ICT, page 197-201. IEEE, (2019)Modeling the overall quality of experience on the basis of underlying quality dimensions., , and . QoMEX, page 1-6. IEEE, (2017)Impact of FEC codes on speech communication quality using WB E-model algorithm., , , , and . Wireless Days, page 1-4. IEEE, (2019)Non-Intrusive Estimation Model for the Speech-Quality Dimension Loudness., , , and . ITG Symposium on Speech Communication, page 1-5. IEEE, (2016)