The History of Speech Recognition to the Year 2030
arXiv:2108.00084
Abstract
The decade from 2010 to 2020 saw remarkable improvements in automatic speech recognition. Many people now use speech recognition on a daily basis, for example to perform voice search queries, send text messages, and interact with voice assistants like Amazon Alexa and Siri by Apple. Before 2010 most people rarely used speech recognition. Given the remarkable changes in the state of speech recognition over the previous decade, what can we expect over the coming decade? I attempt to forecast the state of speech recognition research and applications by the year 2030. While the changes to general speech recognition accuracy will not be as dramatic as in the previous decade, I suggest we have an exciting decade of progress in speech technology ahead of us.
References in corpus (7)
- Bootstrap your own latent: A new approach to self-supervised Learning
- Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
- Attention-Based Models for Speech Recognition
- Achieving Human Parity in Conversational Speech Recognition
- Pushing the Limits of Semi-Supervised Learning for Automatic Speech Recognition
- Iterative Pseudo-Labeling for Speech Recognition
- Differentiable Weighted Finite-State Transducers