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Automatic Speech Feature Learning for Continuous Prediction of Customer Satisfaction in Contact Center Phone Calls.

, , , , and . IberSPEECH, volume 10077 of Lecture Notes in Computer Science, page 255-265. (2016)

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Flexible Stand-Alone Keyword Recognition Application Using Dynamic Time Warping., , and . IberSPEECH, volume 8854 of Lecture Notes in Computer Science, page 158-167. Springer, (2014)Phoneme-Lattice to Phoneme-Sequence Matching Algorithm Based on Dynamic Programming., , , and . IberSPEECH, volume 8854 of Lecture Notes in Computer Science, page 99-108. Springer, (2014)On the use of agglomerative and spectral clustering in speaker diarization of meetings., and . Odyssey, page 130-137. ISCA, (2012)Connectionist Transformation Network Features for Speaker Recognition., and . Odyssey, page 5. ISCA, (2010)The use of long-term features for GMM- and i-vector-based speaker diarization systems., , and . EURASIP J. Audio, Speech and Music Processing, (2018)Detection of speech events and speaker characteristics through photo-plethysmographic signal neural processing., , and . CoRR, (2019)Efficient Keyword Spotting by Capturing Long-Range Interactions with Temporal Lambda Networks., , , , and . ASRU, page 146-153. IEEE, (2021)Inferring social relationships in a phone call from a single party's speech., , and . ICASSP, page 4843-4847. IEEE, (2014)Automatic Speech Feature Learning for Continuous Prediction of Customer Satisfaction in Contact Center Phone Calls., , , , and . IberSPEECH, volume 10077 of Lecture Notes in Computer Science, page 255-265. (2016)A Reality Check on Inference at Mobile Networks Edge., , , , , , , , and . EdgeSys@EuroSys, page 54-59. ACM, (2019)