Α Benchmarking of IBM, Google and Wit Automatic Speech Recognition Systems - Artificial Intelligence Applications and Innovations
Conference Papers Year : 2020

Α Benchmarking of IBM, Google and Wit Automatic Speech Recognition Systems

Foteini Filippidou
  • Function : Author
  • PersonId : 1242570
Lefteris Moussiades
  • Function : Author
  • PersonId : 1242571

Abstract

As the requirements for automatic speech recognition are continually increasing, the demand for accuracy and efficiency is also of particular interest. In this paper, we present most of the well-known Automated Speech Recognition systems (ASR), and we benchmark three of them, namely the IBM Watson, Google, and Wit, using the WER, Hper, and Rper error metrics. The experimental results show that Google’s automatic speech recognition performs better among the three systems. We intend to extend the benchmarking both to include most of the available Automated Speech Recognition systems and increase our test data.
Fichier principal
Vignette du fichier
497040_1_En_7_Chapter.pdf (255.8 Ko) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-04050587 , version 1 (29-03-2023)

Licence

Identifiers

Cite

Foteini Filippidou, Lefteris Moussiades. Α Benchmarking of IBM, Google and Wit Automatic Speech Recognition Systems. 16th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Jun 2020, Neos Marmaras, Greece. pp.73-82, ⟨10.1007/978-3-030-49161-1_7⟩. ⟨hal-04050587⟩
29 View
69 Download

Altmetric

Share

More