Search Results for author:
Found 7 papers, 3 papers with code
Learning from Flawed Data: Weakly Supervised Automatic Speech Recognition
Training automatic speech recognition (ASR) systems requires large amounts of well-curated paired data.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Alternative Pseudo-Labeling for Semi-Supervised Automatic Speech Recognition
Firstly, a generalized CTC loss function is introduced to handle noisy pseudo-labels by accepting alternative tokens in the positions of incorrect tokens.
HK-LegiCoST: Leveraging Non-Verbatim Transcripts for Speech Translation
We introduce HK-LegiCoST, a new three-way parallel corpus of Cantonese-English translations, containing 600+ hours of Cantonese audio, its standard traditional Chinese transcript, and English translation, segmented and aligned at the sentence level.
Bypass Temporal Classification: Weakly Supervised Automatic Speech Recognition with Imperfect Transcripts
Imperfectly transcribed speech is a prevalent issue in human-annotated speech corpora, which degrades the performance of ASR models.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
EURO: ESPnet Unsupervised ASR Open-source Toolkit
This paper describes the ESPnet Unsupervised ASR Open-source Toolkit (EURO), an end-to-end open-source toolkit for unsupervised automatic speech recognition (UASR).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Bridging Speech and Textual Pre-trained Models with Unsupervised ASR
To be specific, we propose to use unsupervised automatic speech recognition (ASR) as a connector that bridges different modalities used in speech and textual pre-trained models.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Decoupling recognition and transcription in Mandarin ASR
Much of the recent literature on automatic speech recognition (ASR) is taking an end-to-end approach.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
