By contrast, this paper aims to investigate the task of end-to-end speech recognition and disfluency removal. We specifically explore whether it is possible to ...
Sep 22, 2020 · Abstract:Disfluency detection is usually an intermediate step between an automatic speech recognition (ASR) system and a downstream task.
By con- trast, this paper aims to investigate the task of end-to-end speech recognition and disfluency removal. We specifically explore whether it is ...
Sep 8, 2023 · Abstract page for arXiv paper 2309.04516: End-to-End Speech Recognition and Disfluency Removal with Acoustic Language Model Pretraining.
A new metric for evaluating end-to-end speech recognition and disfluency removal systems - pariajm/e2e-asr-and-disfluency-removal-evaluator.
Our proposed method replaces disfluent phenomena in the transcription of speech data used for training with two types of labels, filler (＃) and hesitation (＠) ...
It is shown that end-to-end models do learn to directly generate fluent transcripts; however, their performance is slightly worse than a baseline pipeline ...
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In [5] , the authors try to develop a speech recognizer that would generate fluent transcriptions directly from disfluent speech, by implicitly skipping ...
We compare disfluency removal as a post-processing step, using filtering (Filter) and monolingual translation (MonoMT). •Filter requires labeled spans and may ...
Nov 18, 2024 · 2023] propose an end-to-end approach for speech transcription with disflu- ency removal using a large-scale pre-trained HuBERT acoustic model.