Interactive Natural Language Processing (iNLP) has emerged as a novel paradigm within
the field of NLP, aimed at addressing limitations in existing frameworks while aligning with …

Purpose: A major barrier to the wider use of language sample analysis (LSA) is the fact that
transcription is very time intensive. Methods that can reduce the required time and effort …

We present BARTpho with two versions, BARTpho-syllable and BARTpho-word, which are
the first public large-scale monolingual sequence-to-sequence models pre-trained for …

Accurate punctuation in written text enables unambiguous communication, minimizing the
risk of misunderstandings. Conversely, faulty punctuation can confuse the intended …

Punctuation restoration is an important task in automatic speech recognition (ASR) which
aim to restore the syntactic structure of generated ASR texts to improve readability. While …

In clinical dictation, utterances after automatic speech recognition (ASR) without explicit
punctuation marks may lead to the misunderstanding of dictated reports. To give a precise …

Text editing, such as grammatical error correction, arises naturally from imperfect textual
data. Recent works frame text editing as a multi-round sequence tagging task, where …

Mobile devices and social media platforms make communication faster than humans have
had before, thanks to the technologies such as automatic speech recognition (ASR) …

To accomplish the punctuation restoration task, most existing approaches focused on
leveraging extra information (eg, part-of-speech tags) or addressing the class imbalance …

Previous studies demonstrate that part-of-speech (POS) tags are helpful for punctuation
restoration tasks. However, extra computation cost will be needed during decoding, due to …