Error correction techniques have been used to refine the output sentences from automatic
speech recognition (ASR) models and achieve a lower word error rate (WER) than original …

ASR error correction continues to serve as an important part of post-processing for speech
recognition systems. Traditionally, these models are trained with supervised training using …

Error correction in automatic speech recognition (ASR) aims to correct those incorrect words
in sentences generated by ASR models. Since recent ASR models usually have low word …

With the growing popularity of smart speakers, such as Amazon Alexa, speech is becoming
one of the most important modes of human-computer interaction. Automatic speech …

Modern Automatic Speech Recognition (ASR) systems can achieve high performance in
terms of recognition accuracy. However, a perfectly accurate transcript still can be …

Error correction is widely used in automatic speech recognition (ASR) to post-process the
generated sentence, and can further reduce the word error rate (WER). Although multiple …

Text error correction aims to correct the errors in text sequences such as those typed by
humans or generated by speech recognition models. Previous error correction methods …

In the field of Automatic Speech Recognition (ASR), Grammatical Error Correction (GEC)
can be used to correct errors in recognition results of ASR systems and whereby it further …

Automatic speech recognition (ASR) systems often make unrecoverable errors due to
subsystem pruning (acoustic, language and pronunciation models); for example, pruning …

As speech recognition model sizes and training data requirements grow, it is increasingly
common for systems to only be available via APIs from online service providers rather than …