Nothing Special   »   [go: up one dir, main page]
Skip to main content
We gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate
arXiv logo
Cornell University Logo

Computer Science > Computation and Language

arXiv:2410.09456 (cs)
[Submitted on 12 Oct 2024]

Title:Automatic Speech Recognition with BERT and CTC Transformers: A Review

Authors:Noussaiba Djeffal, Hamza Kheddar, Djamel Addou, Ahmed Cherif Mazari, Yassine Himeur
View PDF HTML (experimental)
Abstract:This review paper provides a comprehensive analysis of recent advances in automatic speech recognition (ASR) with bidirectional encoder representations from transformers BERT and connectionist temporal classification (CTC) transformers. The paper first introduces the fundamental concepts of ASR and discusses the challenges associated with it. It then explains the architecture of BERT and CTC transformers and their potential applications in ASR. The paper reviews several studies that have used these models for speech recognition tasks and discusses the results obtained. Additionally, the paper highlights the limitations of these models and outlines potential areas for further research. All in all, this review provides valuable insights for researchers and practitioners who are interested in ASR with BERT and CTC transformers.
Subjects: Computation and Language (cs.CL); Audio and Speech Processing (eess.AS)
Cite as: arXiv:2410.09456 [cs.CL]
  (or arXiv:2410.09456v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2410.09456
Journal reference: 2023 2nd International Conference on Electronics, Energy and Measurement (IC2EM)
Related DOI: https://doi.org/10.1109/IC2EM59347.2023.10419784

Submission history

From: Hamza Kheddar [view email]
[v1] Sat, 12 Oct 2024 09:27:48 UTC (1,206 KB)
Full-text links:

Access Paper:

license icon view license
Current browse context:
cs.CL
< prev   |   next >
new | recent | 2024-10
Change to browse by:
cs
eess
eess.AS

References & Citations

export BibTeX citation

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)