vistec-ser:使用由AIS和VISTEC-DEPA AIResearch Institute泰国赞助的PyTorch进行语音情感识别-源码

上传者: 42151599 | 上传时间: 2021-05-28 17:45:10 | 文件大小: 8.85MB | 文件类型: ZIP
Vistec-AIS语音情感识别 语音情感识别模型及基于Pytorch的推理 安装 从皮皮 pip install vistec-ser 从来源 git clone https://github.com/tann9949/vistec-ser.git cd vistec-ser python setup.py install 用法 使用THAI SER数据集进行培训 我们提供了Google合作实验室示例,用于使用我们的存储库训练。 使用提供的脚本进行培训 请注意,当前,此工作流程仅支持预加载的功能。 因此,这可能会产生〜2 Gb或RAM的额外开销。 运行实验。 运行以下命令 由于有80个录音室录音和20个变焦录音。 我们将数据集分为10个工作室,每组10个工作室。 然后使用k折交叉验证方法进行评估。 我们提供2 k倍的实验:包括和不包括缩放记录。 可以在配置文件中配置它(请参阅examp

文件下载

资源详情

[{"title":"( 37 个子文件 8.85MB ) vistec-ser:使用由AIS和VISTEC-DEPA AIResearch Institute泰国赞助的PyTorch进行语音情感识别-源码","children":[{"title":"vistec-ser-main","children":[{"title":"figures","children":[{"title":"server.gif <span style='color:#111;'> 13.01MB </span>","children":null,"spread":false}],"spread":true},{"title":".github","children":[{"title":"ISSUE_TEMPLATE","children":[{"title":"bug_report.md <span style='color:#111;'> 834B </span>","children":null,"spread":false},{"title":"feature_request.md <span style='color:#111;'> 595B </span>","children":null,"spread":false}],"spread":true},{"title":"workflows","children":[{"title":"python-publish.yml <span style='color:#111;'> 867B </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"vistec_ser","children":[{"title":"utils","children":[{"title":"utils.py <span style='color:#111;'> 1.19KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false}],"spread":true},{"title":"models","children":[{"title":"layers","children":[{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"rnn.py <span style='color:#111;'> 1.99KB </span>","children":null,"spread":false}],"spread":true},{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"network.py <span style='color:#111;'> 6.02KB </span>","children":null,"spread":false},{"title":"base_model.py <span style='color:#111;'> 2.14KB </span>","children":null,"spread":false}],"spread":true},{"title":"evaluation","children":[{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"evaluate.py <span style='color:#111;'> 1.03KB </span>","children":null,"spread":false}],"spread":true},{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"examples","children":[{"title":"evaluate_emodb.py <span style='color:#111;'> 2.46KB </span>","children":null,"spread":false},{"title":"thaiser.yaml <span style='color:#111;'> 765B </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"server.py <span style='color:#111;'> 1.34KB </span>","children":null,"spread":false},{"title":"train_fold_aisser.py <span style='color:#111;'> 4.73KB </span>","children":null,"spread":false},{"title":"emodb.yaml <span style='color:#111;'> 528B </span>","children":null,"spread":false},{"title":"train_aisser.py <span style='color:#111;'> 3.68KB </span>","children":null,"spread":false}],"spread":true},{"title":"inference","children":[{"title":"inference.py <span style='color:#111;'> 1.87KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false}],"spread":true},{"title":"data","children":[{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"datasets","children":[{"title":"thaiser.py <span style='color:#111;'> 17.47KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false},{"title":"emodb.py <span style='color:#111;'> 3.21KB </span>","children":null,"spread":false}],"spread":true},{"title":"features","children":[{"title":"transform.py <span style='color:#111;'> 6.76KB </span>","children":null,"spread":false},{"title":"padding.py <span style='color:#111;'> 1.26KB </span>","children":null,"spread":false},{"title":"__init__.py <span style='color:#111;'> 0B </span>","children":null,"spread":false}],"spread":true},{"title":"ser_slice_dataset.py <span style='color:#111;'> 7.21KB </span>","children":null,"spread":false},{"title":"ser_dataset.py <span style='color:#111;'> 2.86KB </span>","children":null,"spread":false}],"spread":true}],"spread":true},{"title":"LICENSE <span style='color:#111;'> 11.09KB </span>","children":null,"spread":false},{"title":"setup.cfg <span style='color:#111;'> 39B </span>","children":null,"spread":false},{"title":"setup.py <span style='color:#111;'> 1.24KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 2.91KB </span>","children":null,"spread":false},{"title":".gitignore <span style='color:#111;'> 104B </span>","children":null,"spread":false}],"spread":true}],"spread":true}]

评论信息

免责申明

【只为小站】的资源来自网友分享,仅供学习研究,请务必在下载后24小时内给予删除,不得用于其他任何用途,否则后果自负。基于互联网的特殊性,【只为小站】 无法对用户传输的作品、信息、内容的权属或合法性、合规性、真实性、科学性、完整权、有效性等进行实质审查;无论 【只为小站】 经营者是否已进行审查,用户均应自行承担因其传输的作品、信息、内容而可能或已经产生的侵权或权属纠纷等法律责任。
本站所有资源不代表本站的观点或立场,基于网友分享,根据中国法律《信息网络传播权保护条例》第二十二条之规定,若资源存在侵权或相关问题请联系本站客服人员,zhiweidada#qq.com,请把#换成@,本站将给予最大的支持与配合,做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明