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Performance vs. hardware requirements in state-of-the-art automatic speech recognition
2021
EURASIP Journal on Audio, Speech, and Music Processing
AbstractThe last decade brought significant advances in automatic speech recognition (ASR) thanks to the evolution of deep learning methods. ASR systems evolved from pipeline-based systems, that modeled hand-crafted speech features with probabilistic frameworks and generated phone posteriors, to end-to-end (E2E) systems, that translate the raw waveform directly into words using one deep neural network (DNN). The transcription accuracy greatly increased, leading to ASR technology being
doi:10.1186/s13636-021-00217-4
fatcat:7yfquu7irrci3ewug6ijoseduq