We introduce a new collection of spoken English audio suitable for training speech recognition systems under limited or no supervision. It is derived from open-source audio …
YS Chuang, CL Liu, HY Lee, L Lee - arXiv preprint arXiv:1910.11559, 2019 - arxiv.org
While various end-to-end models for spoken language understanding tasks have been explored recently, this paper is probably the first known attempt to challenge the very difficult …
Text to speech (TTS) and automatic speech recognition (ASR) are two dual tasks in speech processing and both achieve impressive performance thanks to the recent advance in deep …
Recently, speech-text pre-training methods have shown remarkable success in many speech and natural language processing tasks. However, most previous pre-trained models …
Producing a large annotated speech corpus for training ASR systems remains difficult for more than 95% of languages all over the world which are low-resourced, but collecting a …
N San, M Bartelds, M Browne, L Clifford… - 2021 IEEE Automatic …, 2021 - ieeexplore.ieee.org
Pre-trained speech representations like wav2vec 2.0 are a powerful tool for automatic speech recognition (ASR). Yet many endangered languages lack sufficient data for pre …
S Suyanto, A Arifianto, A Sirwan… - 2020 8th International …, 2020 - ieeexplore.ieee.org
Recent automatic speech recognition (ASR) is commonly developed using deep learning (DL), instead of the Hidden Markov Model (HMM). Many researchers show that DL is much …
T Yu, H Gao, TE Lin, M Yang, Y Wu, W Ma… - arXiv preprint arXiv …, 2023 - arxiv.org
Recently, speech-text pre-training methods have shown remarkable success in many speech and natural language processing tasks. However, most previous pre-trained models …
DH Galatang - International Journal on Electrical …, 2020 - search.ebscohost.com
The syllable-based automatic speech recognition (ASR) systems commonly perform better than the phoneme-based ones. This paper focuses on developing an Indonesian …