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Found 3 papers, 1 papers with code
FitHuBERT: Going Thinner and Deeper for Knowledge Distillation of Speech Self-Supervised Learning
Our method reduces the model to 23. 8% in size and 35. 9% in inference time compared to HuBERT.
Multi-Task Network for Noise-Robust Keyword Spotting and Speaker Verification using CTC-based Soft VAD and Global Query Attention
Keyword spotting (KWS) and speaker verification (SV) have been studied independently although it is known that acoustic and speaker domains are complementary.
Additional Shared Decoder on Siamese Multi-view Encoders for Learning Acoustic Word Embeddings
Acoustic word embeddings --- fixed-dimensional vector representations of arbitrary-length words --- have attracted increasing interest in query-by-example spoken term detection.
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