Acoustic modeling based on deep learning for low-resource speech recognition: An overview

C Yu, M Kang, Y Chen, J Wu, X Zhao - IEEE Access, 2020 - ieeexplore.ieee.org
The polarization of world languages is becoming more and more obvious. Many languages,
mainly endangered languages, are of low-resource attribute due to lack of information. Both …

Comprehensive literature review on children automatic speech recognition system, acoustic linguistic mismatch approaches and challenges

R Sobti, K Guleria, V Kadyan - Multimedia Tools and Applications, 2024 - Springer
Abstract Automatic Speech Recognition (ASR) system for children is as important as for
adults since children are more dependent on these systems nowadays, such as computer …

Dynamic acoustic unit augmentation with bpe-dropout for low-resource end-to-end speech recognition

A Laptev, A Andrusenko, I Podluzhny, A Mitrofanov… - Sensors, 2021 - mdpi.com
With the rapid development of speech assistants, adapting server-intended automatic
speech recognition (ASR) solutions to a direct device has become crucial. For on-device …

Towards a competitive end-to-end speech recognition for CHiME-6 dinner party transcription

A Andrusenko, A Laptev, I Medennikov - arxiv preprint arxiv:2004.10799, 2020 - arxiv.org
While end-to-end ASR systems have proven competitive with the conventional hybrid
approach, they are prone to accuracy degradation when it comes to noisy and low-resource …

Multi-task and transfer learning in low-resource speech recognition

J Meyer - 2019 - search.proquest.com
This thesis investigates methods for Acoustic Modeling in Automatic Speech Recognition,
assuming limited access to training data in the target domain. The Acoustic Models of …

Exploration of end-to-end asr for openstt–russian open speech-to-text dataset

A Andrusenko, A Laptev, I Medennikov - Speech and Computer: 22nd …, 2020 - Springer
This paper presents an exploration of end-to-end automatic speech recognition systems
(ASR) for the largest open-source Russian language data set–OpenSTT. We evaluate …

[PDF][PDF] Robust speech recognition for low-resource languages

A Romanenko - 2022 - oparu.uni-ulm.de
Process of human-machine interaction is an integral part of everyday human life in a modern
world. The various interfaces are intended to facilitate this interaction and provide maximum …

Space-and-speaker-aware acoustic modeling with effective data augmentation for recognition of multi-array conversational speech

L Chai, H Chen, J Du, QF Liu, CH Lee - Speech Communication, 2023 - Elsevier
We propose a space-and-speaker-aware (SSA) approach to acoustic modeling (AM),
denoted as SSA-AM, to improve system performances of automatic speech recognition …

Improving Tibetan End-To-End Speech Recognition with Transfer Learning

Y Li, Q Zhang, G Li - Journal of Physics: Conference Series, 2023 - iopscience.iop.org
End-to-end architecture has shown outstanding performance in the field of speech
recognition, but achieving such performance typically requires a large amount of annotated …

Applicability of End-to-End Deep Neural Architecture to Sinhala Speech Recognition

B Gamage, R Pushpananda… - … Journal on Advances …, 2024 - journal.icter.org
This research presents a study on the application of end-to-end deep learning models for
Automatic Speech Recognition in the Sinhala language, which is characterized by its high …