wav2vec2.0提取声学特征

wav2vec2.0是一种基于自监督学习的语音特征提取方法，通过训练未标注的语音数据，学习到音频信号的有用表示。通过wav2vec2.0的中文fine-tuning流程，开发者可以在自己的数据集上进行微调，以获得在特定场景中表现更优秀的模型。具体实现上，可以参考torchAudio官方给出的wav2vec2.0的代码样例，理解其中的相关源码和具体代码实现。通过这些方法，可以提取出wav2vec2.0的声学特征。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
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- *3* [运行torchAudio下的wav2vec2.0样例](https://blog.csdn.net/weixin_43142450/article/details/123831419)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v93^chatsearchT3_1"}}] [.reference_item style="max-width: 50%"]
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