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- HuBERT：基于BERT的自监督 (self-supervised)语音表示学习
本文我将介绍HuBERT，一个基于BERT的自监督语音表示学习的工作。 近年来基于自监督的表示学习在NLP领域非常流行，但语音的表示学习和NLP不同面临很多其它的挑战。
- HuBERT: Self-Supervised Speech Representation Learning by Masked . . .
To deal with these three problems, we propose the Hidden-Unit BERT (HuBERT) approach for self-supervised speech representation learning, which utilizes an offline clustering step to provide aligned target labels for a BERT-like prediction loss
- GitHub - bshall hubert: HuBERT content encoders for: A Comparison of . . .
Training and inference scripts for the HuBERT content encoders in A Comparison of Discrete and Soft Speech Units for Improved Voice Conversion For more details see soft-vc
- Hubert US
Hubert is the leader in food merchandising, tailored solutions and quality service across the US and Canada Home to more than 130,000 products, Hubert com offers top brands like Vollrath, Cambro and Vulcan
- Hubert - Hugging Face 文档
Hubert 是一个语音模型，它接受一个与语音信号原始波形相对应的浮点数组。 Hubert 模型使用联结主义时间分类 (CTC) 进行微调，因此模型输出必须使用 `Wav2Vec2CTCTokenizer` 进行解码。
- Hubert — transformers 4. 7. 0 documentation - Hugging Face
Using a 1B parameter model, HuBERT shows up to 19% and 13% relative WER reduction on the more challenging dev-other and test-other evaluation subsets Tips: Hubert is a speech model that accepts a float array corresponding to the raw waveform of the speech signal
- HuBERT 项目安装和配置指南 - CSDN博客
HuBERT（Hidden Unit BERT）是一个用于语音表示学习的自监督模型，主要用于 语音转换 任务。 该项目提供了训练和推理脚本，用于比较离散和软语音单元在语音转换中的效果。
- HuBERT论文解读 - 知乎
论文提出了一种名为 HuBERT （Hidden-Unit BERT）的自监督语音表示学习方法，通过掩码预测隐藏单元的聚类标签，解决了语音信号中的三个核心问题：（1）输入语句中多音素共存；（2）预训练阶段缺乏音素词典；（3）音素边界不明确且长度可变。
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