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Found 5 papers, 1 papers with code
Improving Speech Inversion Through Self-Supervised Embeddings and Enhanced Tract Variables
The performance of deep learning models depends significantly on their capacity to encode input features efficiently and decode them into meaningful outputs.
Kid-Whisper: Towards Bridging the Performance Gap in Automatic Speech Recognition for Children VS. Adults
Recent advancements in Automatic Speech Recognition (ASR) systems, exemplified by Whisper, have demonstrated the potential of these systems to approach human-level performance given sufficient data.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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Enhancing Speech Articulation Analysis using a Geometric Transformation of the X-ray Microbeam Dataset
Accurate analysis of speech articulation is crucial for speech analysis.
Masked Autoencoders Are Articulatory Learners
Articulatory recordings track the positions and motion of different articulators along the vocal tract and are widely used to study speech production and to develop speech technologies such as articulatory based speech synthesizers and speech inversion systems.
Audio Data Augmentation for Acoustic-to-articulatory Speech Inversion using Bidirectional Gated RNNs
In this work, we compare and contrast different ways of doing data augmentation and show how this technique improves the performance of articulatory speech inversion not only on noisy speech, but also on clean speech data.
