Search Results for author:
Found 7 papers, 2 papers with code
Is BERT a Cross-Disciplinary Knowledge Learner? A Surprising Finding of Pre-trained Models’ Transferability
This paper investigates whether the power of the models pre-trained on text data, such as BERT, can be transferred to general token sequence classification applications.
DDOS: A MOS Prediction Framework utilizing Domain Adaptive Pre-training and Distribution of Opinion Scores
Mean opinion score (MOS) is a typical subjective evaluation metric for speech synthesis systems.
On the Efficiency of Integrating Self-supervised Learning and Meta-learning for User-defined Few-shot Keyword Spotting
User-defined keyword spotting is a task to detect new spoken terms defined by users.
Membership Inference Attacks Against Self-supervised Speech Models
Recently, adapting the idea of self-supervised learning (SSL) on continuous speech has started gaining attention.
Utilizing Self-supervised Representations for MOS Prediction
In this paper, we use self-supervised pre-trained models for MOS prediction.
Is BERT a Cross-Disciplinary Knowledge Learner? A Surprising Finding of Pre-trained Models' Transferability
This paper investigates whether the power of the models pre-trained on text data, such as BERT, can be transferred to general token sequence classification applications.
BERT's output layer recognizes all hidden layers? Some Intriguing Phenomena and a simple way to boost BERT
Although Bidirectional Encoder Representations from Transformers (BERT) have achieved tremendous success in many natural language processing (NLP) tasks, it remains a black box.
