Do End-to-End Speech Recognition Models Care About Context?
- Resource Type
- Source
- Borgholt, L, Havtorn, J D, Agic, Ž, Søgaard, A, Maaløe, L & Igel, C 2020, Do end-to-end speech recognition models care about context? in Proceedings of the Annual Conference of the International Speech Communication Association . Proceedings of the Annual Conference of the International Speech Communication Association, Interspeech, pp. 4352-4356, Interspeech 2020, Shanghai, China, 25/10/2020 . https://doi.org/10.21437/Interspeech.2020-1750
Borgholt, L, Havtorn, J D, Agic, Ž, Søgaard, A, Maaløe, L & Igel, C 2020, Do end-to-end speech recognition models care about context? in Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH . vol. 2020-October, International Speech Communication Association (ISCA), pp. 4352-4356, 21st Annual Conference of the International Speech Communication Association, INTERSPEECH 2020, Shanghai, China, 25/10/2020 . https://doi.org/10.21437/Interspeech.2020-1750
INTERSPEECH - Subject
FOS: Computer and information sciences Sound (cs.SD) Computer Science - Machine Learning Computer science Speech recognition Context (language use) 010501 environmental sciences 01 natural sciences Computer Science - Sound Machine Learning (cs.LG) Attention-based encoder-decoder 03 medical and health sciences 0302 clinical medicine End-to-end principle Connectionism Connectionist temporal classification Audio and Speech Processing (eess.AS) FOS: Electrical engineering, electronic engineering, information engineering Sensitivity (control systems) 0105 earth and related environmental sciences Computer Science - Computation and Language Automatic speech recognition Contrast (statistics) 030208 emergency & critical care medicine Language model End-to-end speech recognition Computation and Language (cs.CL) Electrical Engineering and Systems Science - Audio and Speech Processing - Language
- English