Natural language processing for smart healthcare
Smart healthcare has achieved significant progress in recent years. Emerging artificial
intelligence (AI) technologies enable various smart applications across various healthcare …
intelligence (AI) technologies enable various smart applications across various healthcare …
Automatic speech recognition using limited vocabulary: A survey
JLKE Fendji, DCM Tala, BO Yenke… - Applied Artificial …, 2022 - Taylor & Francis
ABSTRACT Automatic Speech Recognition (ASR) is an active field of research due to its
large number of applications and the proliferation of interfaces or computing devices that …
large number of applications and the proliferation of interfaces or computing devices that …
Augmented datasheets for speech datasets and ethical decision-making
Speech datasets are crucial for training Speech Language Technologies (SLT); however,
the lack of diversity of the underlying training data can lead to serious limitations in building …
the lack of diversity of the underlying training data can lead to serious limitations in building …
[HTML][HTML] Human-centered neural reasoning for subjective content processing: Hate speech, emotions, and humor
Some tasks in content processing, eg, natural language processing (NLP), like hate or
offensive speech and emotional or funny text detection, are subjective by nature. Each …
offensive speech and emotional or funny text detection, are subjective by nature. Each …
Residual adapters for parameter-efficient ASR adaptation to atypical and accented speech
Automatic Speech Recognition (ASR) systems are often optimized to work best for speakers
with canonical speech patterns. Unfortunately, these systems perform poorly when tested on …
with canonical speech patterns. Unfortunately, these systems perform poorly when tested on …
[PDF][PDF] Disordered Speech Data Collection: Lessons Learned at 1 Million Utterances from Project Euphonia.
RL MacDonald, PP Jiang, J Cattiau, R Heywood… - Interspeech, 2021 - isca-archive.org
Speech samples from over 1000 individuals with impaired speech have been submitted for
Project Euphonia, aimed at improving automated speech recognition systems for disordered …
Project Euphonia, aimed at improving automated speech recognition systems for disordered …
From user perceptions to technical improvement: Enabling people who stutter to better use speech recognition
Consumer speech recognition systems do not work as well for many people with speech
differences, such as stuttering, relative to the rest of the general population. However, what …
differences, such as stuttering, relative to the rest of the general population. However, what …
Investigating self-supervised pretraining frameworks for pathological speech recognition
We investigate the performance of self-supervised pretraining frameworks on pathological
speech datasets used for automatic speech recognition (ASR). Modern end-to-end models …
speech datasets used for automatic speech recognition (ASR). Modern end-to-end models …
Speaker adaptation using spectro-temporal deep features for dysarthric and elderly speech recognition
Despite the rapid progress of automatic speech recognition (ASR) technologies targeting
normal speech in recent decades, accurate recognition of dysarthric and elderly speech …
normal speech in recent decades, accurate recognition of dysarthric and elderly speech …
Exploring self-supervised pre-trained asr models for dysarthric and elderly speech recognition
Automatic recognition of disordered and elderly speech remains a highly challenging task to
date due to the difficulty in collecting such data in large quantities. This paper explores a …
date due to the difficulty in collecting such data in large quantities. This paper explores a …