精通
英语
和
开源
，
擅长
开发
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胸怀四海
第一信赖
精通
英语
和
开源
，
擅长
开发
与
培训
，
胸怀四海
第一信赖
I'm a student. For my work, I have to use Kaldi. I'm working on a project about recognizing in realtime and offline with DNN. I'm asking if somebody knows that it need a big storage to speech recognize offline? So that I will know I should bring a hard drive or not.我是学生。对于我的工作，我必须使用Kaldi。我正在进行一个有关使用DNN进行实时和脱机识别的项目。我在问是否有人知道需要大容量存储才能离线识别语音？这样我就知道我是否应该带硬盘驱动器。
I'm not sure exactly what you mean when you use the terms "off-line" and "real-time" here - perhaps you could clarify what these terms mean to you.
And perhaps instead of "bring" you mean "buy"? You basically need a Linux system and you need some familiarity with UNIX in order to do this. The
hard drive space requirement depends on how much data you want to train on, but for small databases, a few tens of gigabytes may be enough. For large
databases, to run DNNs you'd need a cluster of computers with GPUs, and I'm guessing from your question that that is not something you have.我不确定 在此处使用“离线”和“实时”这两个术语时的确切含义-也许您可以澄清这些术语对您的含义。
也许不是“带来”，而是“购买”？基本上，您需要一个Linux系统，并且您需要对UNIX有所了解。该硬盘空间要求取决于你想要多少数据来训练的，
但对于小型数据库，几数十GB的可能是不够的。对于大型数据库，要运行DNN，您需要一台具有GPU的计算机集群，而我从您的问题中猜测那不是您所拥有的。
Sorry! Maybe I should clarify how my project is going. I will carry a system with me. The system can collect sound and recognize with Kaldi in real-time. The DNN in Kaldi has been trained completely, so the DNN in system only need to test and recognize. The data system collect won't send to server run the result. I wonder if this process need a big storage or not.
Some of your message is help for me.
Hope this will be clear enough.抱歉! 也许我应该弄清楚我的项目进展如何。我将随身携带一个系统。该系统可以收集声音并通过Kaldi进行实时识别。Kaldi中的DNN已经过全面培训，因此系统中的DNN仅需测试和识别。数据系统收集的结果不会发送到服务器。我想知道此过程是否需要大容量存储。
您的一些信息对我有帮助。
Hm. So you mean real-time decoding on a device without being connected to
a server.
It doesn't require very much storage, except that required to store the DNN
(a few megabytes, maybe), and to store the audio if you want to store this
for logging purposes.
Building usable real-time systems is challenging.I suggest as a starting point you look at the program
online2-wav-nnet2-latgen-faster
and the corresponding example scripts in egs/*/s5/local/online/run_nnet2.sh
嗯 因此，您的意思是无需连接服务器即可在设备上进行实时解码。
它不需要太多的存储，除了需要存储DNN（也许是几兆字节），以及如果要出于记录目的而存储音频，则需要存储音频。
建立可用的实时系统具有挑战性。
我建议您先看一下online2-wav-nnet2-latgen-faster程序 和egs / * / s5 / local / online / run_nnet2.sh中的相应示例脚本
Thanks a lot! After a discussion with my group members, I got another question. The DNN model won't require much storage. What about the output of DNN after every training data which is big vocabulary. So that it can compare with the test data for recognizing. I am asking that if it needs big storage for output of DNN trained with big data.非常感谢！与小组成员讨论后，我又提出了另一个问题。DNN模型不需要太多存储。每次大词汇量训练数据之后，DNN的输出如何？这样就可以与测试数据进行比较以进行识别。我在问，是否需要大存储量来存储经过大数据训练的DNN。
It won't need a lot of storage, no. You should probably read a bit of
background about speech recognition, e.g. the HTK Book.不需要太多的存储空间。您可能应该阅读一些有关语音识别的背景知识，例如HTK Book。
I have asked someone who use HTK told me that it only need less than 50 MB to store all the model for a data set. So Kaldi is also need about 50 MB ?我曾问过使用HTK的人告诉我，它只需要不到50 MB的空间即可存储数据集的所有模型。那么Kaldi还需要大约50 MB？
It depends on so many things that the question doesn't even make sense.
Before asking any more questions, please do some reading and try to
understand at least a little about how speech recognition works.它取决于很多事情，所以这个问题甚至都没有道理。
在提出任何其他问题之前，请阅读一些内容并尝试至少对语音识别的工作原理有所了解。