[doc]add asr usercase #42
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aspirer
requested changes
Nov 21, 2023
| CurveFS 兼容两种存储后端的特性，使其可以适应不同业务的存储需求，既保证高性能，也控制存储成本。 | ||
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| ### CurveFS 优势 |
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| ### CurveFS 优势 | ||
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| 相较于本地存储而言，CurveFS 具有以下优势: |
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| * 统一管理训练数据,支持多节点共享访问 | ||
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| * 后端接入 NOS低频存储，相比3副本存储每年每 PB 数据存储可节约40%成本，大幅降低 ASR 训练存储成本 |
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这里是3副本。上面是本地。我看他们原来是打算每个节点都放一份训练数据？
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这里是3副本。上面是本地。我看他们原来是打算每个节点都放一份训练数据？
是的
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| * 后端接入 NOS低频存储，相比3副本存储每年每 PB 数据存储可节约40%成本，大幅降低 ASR 训练存储成本 | ||
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| * 支持数据多级缓存，提升训练并发效率 |
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| 作为一个年轻的项目，Curve仍在快速迭代。未来Curve会继续优化在AI和大数据分析场景的适配能力: | ||
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| 与各类AI框架深度集成，提供自动化的数据预热、训练优化等功能,提升AI训练的易用性和效率。 |
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格式需要改善，预览下看看。
fix
wuhongsong
reviewed
Nov 21, 2023
| @@ -0,0 +1,74 @@ | |||
| # CurveFS 助力网易云商，解决 ASR 训练数据增长需求 | |||
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题目建议不要使用ASR缩写 -- 直接用人工智能 语音识别之类的 这样更吸引人？
| 随着语音技术在各行各业的广泛应用，自动语音识别(ASR)正在成为众多云服务商的核心竞争力。 | ||
| 但 ASR 模型的持续优化需要大量训练数据的支持,如何高效管理海量训练数据成为云商面临的一个难题。 | ||
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| 网易云商在发展 ASR 业务过程中，存储面临了巨大挑战。 |
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遇到的这几个困难可以按照 "无序列表 "模式展示
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遇到的这几个困难可以按照 "无序列表 "模式展示
fix
| CurveFS 兼容两种存储后端的特性，使其可以适应不同业务的存储需求，既保证高性能，也控制存储成本。 | ||
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| ### CurveFS 优势 |
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这里可以参考下https://kms.netease.com/article/88340 ， 内容更丰富一些
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这里可以参考下https://kms.netease.com/article/88340 ， 内容更丰富一些
#43
已经使用了？
Signed-off-by: Cyber-SiKu <[email protected]>
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wuhongsong
approved these changes
Nov 22, 2023
aspirer
approved these changes
Nov 22, 2023
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