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Found 7 papers, 2 papers with code
Manipulation of oral cancer speech using neural articulatory synthesis
We present an articulatory synthesis framework for the synthesis and manipulation of oral cancer speech for clinical decision making and alleviation of patient stress.
The Effectiveness of Time Stretching for Enhancing Dysarthric Speech for Improved Dysarthric Speech Recognition
In this paper, we investigate several existing and a new state-of-the-art generative adversarial network-based (GAN) voice conversion method for enhancing dysarthric speech for improved dysarthric speech recognition.
Towards Identity Preserving Normal to Dysarthric Voice Conversion
We present a voice conversion framework that converts normal speech into dysarthric speech while preserving the speaker identity.
An Objective Evaluation Framework for Pathological Speech Synthesis
The development of pathological speech systems is currently hindered by the lack of a standardised objective evaluation framework.
Pathological voice adaptation with autoencoder-based voice conversion
This approach alleviates the evaluation problem one normally has when converting typical speech to pathological speech, as in our approach, the voice conversion (VC) model does not need to be optimised for speech degradation but only for the speaker change.
Quantifying Bias in Automatic Speech Recognition
Practice and recent evidence suggests that the state-of-the-art (SotA) ASRs struggle with the large variation in speech due to e. g., gender, age, speech impairment, race, and accents.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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Detecting and analysing spontaneous oral cancer speech in the wild
3) We set baselines for an oral cancer speech detection task on this dataset.
