Effective human and automatic processing of speech requires recovery of more than just the
words. It also involves recovering phenomena such as sentence boundaries, filler words …

We describe a “direct modeling” approach to using prosody in various speech technology
tasks. The approach does not involve any hand-labeling or modeling of prosodic events …

Enriching speech recognition output with sentence boundaries improves its human
readability and enables further processing by downstream language processing modules …

This paper describes BiLSTM-based models to disfluency detection in speech transcripts
using residual BiLSTM blocks, self-attention, and noisy training approach. Our best model …

We present a discriminative model for detecting disfluencies in spoken language transcripts.
Structurally, our model is a semi-Markov conditional random field with features targeting …

Meetings are a pervasive method of communication within all types of companies and
organizations, and using remote collaboration systems to conduct meetings has increased …

Joint dependency parsing with disfluency detection is an important task in speech language
processing. Recent methods show high performance for this task, although most authors …

Automatic detection of disfluencies in spoken language is important for making speech
recognition output more readable, and for aiding downstream language processing …

This paper describes a transformation-based learning approach to disfluency detection in
speech transcripts using primarily lexical features. Our method produces comparable results …

Prosody is an important cue for identifying dialog acts. In this paper, we show that modeling
the sequence of acoustic–prosodic values as n-gram features with a maximum entropy …