Comparative Layer-Wise Analysis of Self-Supervised Speech Models

Author:

Pasad Ankita1,Shi Bowen1,Livescu Karen1

Affiliation:

1. Toyota Technological Institute at Chicago

Publisher

IEEE

Reference29 articles.

1. wav2vec 2.0: A framework for self-supervised learning of speech representations;baevski;NeurIPS,2020

2. Fast-Slow Transformer for Visually Grounding Speech

3. Self-supervised representation learning for speech using visual grounding and masked language modeling;peng;AAAI Workshop on Self-supervised Learning for Audio and Speech Processing,2022

4. Unsupervised Cross-Lingual Representation Learning for Speech Recognition

5. Layer-Wise Analysis of a Self-Supervised Speech Representation Model

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1. Efficiency-oriented approaches for self-supervised speech representation learning;International Journal of Speech Technology;2024-08-19

2. Speech Representation Analysis Based on Inter- and Intra-Model Similarities;2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW);2024-04-14

3. Layer-Wise Analysis of Self-Supervised Acoustic Word Embeddings: A Study on Speech Emotion Recognition;2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW);2024-04-14

4. Noise Robust Distillation of Self-Supervised Speech Models via Correlation Metrics;2024 IEEE International Conference on Acoustics, Speech, and Signal Processing Workshops (ICASSPW);2024-04-14

5. Understanding Probe Behaviors Through Variational Bounds of Mutual Information;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

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