3 citations · 4 across the 7 of their papers we have counts for
7 papers
Cross-Lingual Conversational Speech Summarization with Large Language Models
Max Nelson, Shannon Wotherspoon, Francis Keith +2
Cross-lingual conversational speech summarization is an important problem, but suffers from a dearth of resources. While transcriptions exist for a number of languages, translated…
TOGGL: Transcribing Overlapping Speech with Staggered Labeling
Chak-Fai Li, William Hartmann, Matthew Snover
Transcribing the speech of multiple overlapping speakers typically requires separating the audio into multiple streams and recognizing each one independently. More recent work join…
Advancing Speech Translation: A Corpus of Mandarin-English Conversational Telephone Speech
Shannon Wotherspoon, William Hartmann, Matthew Snover
This paper introduces a set of English translations for a 123-hour subset of the CallHome Mandarin Chinese data and the HKUST Mandarin Telephone Speech data for the task of speech…
Training Autoregressive Speech Recognition Models with Limited in-domain Supervision
Chak-Fai Li, Francis Keith, William Hartmann +1
Advances in self-supervised learning have significantly reduced the amount of transcribed audio required for training. However, the majority of work in this area is focused on read…
Combining Unsupervised and Text Augmented Semi-Supervised Learning for Low Resourced Autoregressive Speech Recognition
Chak-Fai Li, Francis Keith, William Hartmann +1
Recent advances in unsupervised representation learning have demonstrated the impact of pretraining on large amounts of read speech. We adapt these techniques for domain adaptation…
Overcoming Domain Mismatch in Low Resource Sequence-to-Sequence ASR Models using Hybrid Generated Pseudotranscripts
Chak-Fai Li, Francis Keith, William Hartmann +2
Sequence-to-sequence (seq2seq) models are competitive with hybrid models for automatic speech recognition (ASR) tasks when large amounts of training data are available. However, da…
Using heterogeneity in semi-supervised transcription hypotheses to improve code-switched speech recognition
Andrew Slottje, Shannon Wotherspoon, William Hartmann +2
Modeling code-switched speech is an important problem in automatic speech recognition (ASR). Labeled code-switched data are rare, so monolingual data are often used to model code-s…