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Audio self-supervised learning: A survey
Similar to humans' cognitive ability to generalize knowledge and skills, self-supervised
learning (SSL) targets discovering general representations from large-scale data. This …
learning (SSL) targets discovering general representations from large-scale data. This …
Wavlm: Large-scale self-supervised pre-training for full stack speech processing
Self-supervised learning (SSL) achieves great success in speech recognition, while limited
exploration has been attempted for other speech processing tasks. As speech signal …
exploration has been attempted for other speech processing tasks. As speech signal …
Comparative layer-wise analysis of self-supervised speech models
Many self-supervised speech models, varying in their pre-training objective, input modality,
and pre-training data, have been proposed in the last few years. Despite impressive …
and pre-training data, have been proposed in the last few years. Despite impressive …
A survey of reasoning with foundation models
Reasoning, a crucial ability for complex problem-solving, plays a pivotal role in various real-
world settings such as negotiation, medical diagnosis, and criminal investigation. It serves …
world settings such as negotiation, medical diagnosis, and criminal investigation. It serves …
Ml-superb: Multilingual speech universal performance benchmark
Speech processing Universal PERformance Benchmark (SUPERB) is a leaderboard to
benchmark the performance of Self-Supervised Learning (SSL) models on various speech …
benchmark the performance of Self-Supervised Learning (SSL) models on various speech …
A large-scale evaluation of speech foundation models
The foundation model paradigm leverages a shared foundation model to achieve state-of-
the-art (SOTA) performance for various tasks, requiring minimal downstream-specific data …
the-art (SOTA) performance for various tasks, requiring minimal downstream-specific data …
What do self-supervised speech models know about words?
Many self-supervised speech models (S3Ms) have been introduced over the last few years,
improving performance and data efficiency on various speech tasks. However, these …
improving performance and data efficiency on various speech tasks. However, these …
Advancing large language models to capture varied speaking styles and respond properly in spoken conversations
In spoken dialogue, even if two current turns are the same sentence, their responses might
still differ when they are spoken in different styles. The spoken styles, containing …
still differ when they are spoken in different styles. The spoken styles, containing …
On the utility of self-supervised models for prosody-related tasks
Self-Supervised Learning (SSL) from speech data has produced models that have achieved
remarkable performance in many tasks, and that are known to implicitly represent many …
remarkable performance in many tasks, and that are known to implicitly represent many …
Generative pre-training for speech with flow matching
Generative models have gained more and more attention in recent years for their
remarkable success in tasks that required estimating and sampling data distribution to …
remarkable success in tasks that required estimating and sampling data distribution to …