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Found 5 papers, 1 papers with code
Adapting self-supervised models to multi-talker speech recognition using speaker embeddings
Self-supervised learning (SSL) methods which learn representations of data without explicit supervision have gained popularity in speech-processing tasks, particularly for single-talker applications.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Updating Only Encoders Prevents Catastrophic Forgetting of End-to-End ASR Models
In this paper, we present an incremental domain adaptation technique to prevent catastrophic forgetting for an end-to-end automatic speech recognition (ASR) model.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Semi-Supervised Training with Pseudo-Labeling for End-to-End Neural Diarization
To evaluate our proposed method, we conduct the experiments of model adaptation using labeled and unlabeled data.
End-to-End Speaker Diarization Conditioned on Speech Activity and Overlap Detection
In this paper, we present a conditional multitask learning method for end-to-end neural speaker diarization (EEND).
Feature Enhancement with Deep Feature Losses for Speaker Verification
On BabyTrain corpus, we observe relative gains of 10. 38% and 12. 40% in minDCF and EER respectively.
