blocks|key|1010027|text|不要试图这样做|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1010028|诗歌不能很好地融合|1010029|用金属和钻头|1010030|更严重的是，好的haiku+(甚至是坏的haiku)更多的是浓缩意义和形象，而不是计算音节。它通常也是基于从自然中收集的主题。随机的单词生成和音节统计会让你胡言乱语，但不会有诗意...|1010031|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|J|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|K|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|L|8|@]|9|@]|A|$]]|$1|F|3|G|5|6|7|M|8|@]|9|@]|A|$]]|$1|H|3|-4|5|6|7|N|8|@]|9|@]|A|$]]]|I|$]]

Do not attempt it 
Poetry does not mix well 
With metal and bits

More seriously, good haiku (and even bad haiku) is a lot more about condensing meaning and imagery than counting syllables. It is generally also based on themes gathered from nature. Random word generation and syllable counting will get you measured gibberish, but not poetry...

blocks|key|3502202|text|测量音节|type|unstyled|depth|inlineStyleRanges|entityRanges|data|3502203|理解语义流|3502204|你的目标可以实现|3502205|entityMap^0|0|0|0^^$0|@$1|2|3|4|5|6|7|H|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|I|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|J|8|@]|9|@]|A|$]]|$1|F|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|G|$]]

Measure syllables 
Understand semantic flow 
Your goal can be met

blocks|key|285078|text|首先，您需要了解Markov+chains，其次，有一本关于计算机生成的诗歌的书，名为Virtual+Muse。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|285079|entityMap|0|LINK|mutability|MUTABLE|url|http://en.wikipedia.org/wiki/Markov_chain|1|https://rads.stackoverflow.com/amzn/click/com/0819522392^0|8|D|0|17|C|1|0^^$0|@$1|2|3|4|5|6|7|N|8|@]|9|@$A|O|B|P|1|Q]|$A|R|B|S|1|T]]|C|$]]|$1|D|3|-4|5|6|7|U|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]|L|$5|G|H|I|C|$J|M]]]]

First, you'll want to look into <a href="http://en.wikipedia.org/wiki/Markov_chain" rel="noreferrer">Markov chains</a>, and second, there's a book about computer-generated poetry called <a href="https://rads.stackoverflow.com/amzn/click/com/0819522392" rel="noreferrer" rel="nofollow noreferrer">Virtual Muse</a>.

blocks|key|4349694|text|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4349695|count+syllables|unordered-list-item|4349696|randomly+generate+words|4349697|arrange+sensibly|4349698|4349699|entityMap^0|0|0|0|0|0^^$0|@$1|2|3|-4|4|5|6|K|7|@]|8|@]|9|$]]|$1|A|3|B|4|C|6|L|7|@]|8|@]|9|$]]|$1|D|3|E|4|C|6|M|7|@]|8|@]|9|$]]|$1|F|3|G|4|C|6|N|7|@]|8|@]|9|$]]|$1|H|3|-4|4|5|6|O|7|@]|8|@]|9|$]]|$1|I|3|-4|4|5|6|P|7|@]|8|@]|9|$]]]|J|$]]

<ul>
<li>count the syllables</li>
<li>randomly generate words</li>
<li>arrange sensibly</li>
</ul>

blocks|key|285602|text|我会注意到，Haikus很简单|type|unstyled|depth|inlineStyleRanges|entityRanges|data|285603|解决方案文档化，功能死记硬背|285604|它们做得过火了，而且很俗气|285605|编码太简单了|285606|给我编个打油诗，然后我会投票|285607|//我真的很喜欢haikus|285608|entityMap^0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|N|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|O|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|P|8|@]|9|@]|A|$]]|$1|F|3|G|5|6|7|Q|8|@]|9|@]|A|$]]|$1|H|3|I|5|6|7|R|8|@]|9|@]|A|$]]|$1|J|3|K|5|6|7|S|8|@]|9|@]|A|$]]|$1|L|3|-4|5|6|7|T|8|@]|9|@]|A|$]]]|M|$]]

Haikus are easy, that I'll note 
Solutions well documented, and functions rote 
They're overdone and cheesy 
Coding far too easy 
Code me a limerick, then I'll vote

//I actually like haikus

blocks|key|4349569|text|不是所有的haikus都有相同数量的音节，但它是一个起点。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4349570|就实际选择单词而言，我认为词性不会是我开始的地方。相反，我会关注Markov+chains,+and+train+your+vocabulary+on+existing+haikus.|offset|length|4349571|entityMap|0|LINK|mutability|MUTABLE|url|http://www.cs.umd.edu/class/spring2007/cmsc132/Projects/p6/p6.html^0|0|W|1O|0|0^^$0|@$1|2|3|4|5|6|7|N|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|O|8|@]|9|@$D|P|E|Q|1|R]]|A|$]]|$1|F|3|-4|5|6|7|S|8|@]|9|@]|A|$]]]|G|$H|$5|I|J|K|A|$L|M]]]]

Not all haikus have the same number of syllables, but it's a place to start.

In terms of actually picking the words, I think that parts of speech would not be the place where I would start. Instead, I would look at <a href="http://www.cs.umd.edu/class/spring2007/cmsc132/Projects/p6/p6.html" rel="nofollow noreferrer">Markov chains, and train your vocabulary on existing haikus.</a>

blocks|key|3502642|text|在Haiku+Village上，我们拥有以各种方式轻松完成此操作的技术。一种想法是简单地阅读全球推特订阅，并检测无意中的haikus。由于后端也有一个字典，可能会产生有问题的haikus，但我认为质量会有所欠缺。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|3502643|我认为如果我们有一个星级系统，那么我想机器学习可以用来决定什么是“好的”。|3502644|entityMap|0|LINK|mutability|MUTABLE|url|http://www.haikuvillage.com/^0|1|D|0|0|0^^$0|@$1|2|3|4|5|6|7|N|8|@]|9|@$A|O|B|P|1|Q]]|C|$]]|$1|D|3|E|5|6|7|R|8|@]|9|@]|C|$]]|$1|F|3|-4|5|6|7|S|8|@]|9|@]|C|$]]]|G|$H|$5|I|J|K|C|$L|M]]]]

On <a href="http://www.haikuvillage.com" rel="noreferrer">Haiku Village</a>, we have the technology to easily do this in a variety of ways. One idea is to simply read the global twitter feed, and detect unintentional haikus. Since the back-end also has a dictionary, it would be possible to produce questionable haikus, but I think the quality would be lacking.

I think if we had a star rating system, then I suppose machine learning could be used to decide what is 'good'.

blocks|key|3502728|text|for+(i+is+0
and+i+is+less+than+thirteen)
print+s+i+plus+plus|type|code-block|depth|inlineStyleRanges|entityRanges|data|syntax|javascript|3502729|unstyled|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|G|8|@]|9|@]|A|$B|C]]|$1|D|3|-4|5|E|7|H|8|@]|9|@]|A|$]]]|F|$]]

<pre><code>for (i is 0
and i is less than thirteen)
print s i plus plus
</code></pre>

blocks|key|3502134|text|实现一种遗传算法，从标注了音节计数的字典中生成haikus，然后付钱让人们阅读，并将其评为适应度函数，机械turk会有所帮助。随着时间的推移，你的程序应该会进化出一些好的。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|3502135|编辑：|3502136|您需要的GA|3502137|以CPU速度发展|3502138|如果你注意健身的话|3502139|entityMap^0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|M|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|N|8|@]|9|@]|A|$]]|$1|F|3|G|5|6|7|O|8|@]|9|@]|A|$]]|$1|H|3|I|5|6|7|P|8|@]|9|@]|A|$]]|$1|J|3|-4|5|6|7|Q|8|@]|9|@]|A|$]]]|K|$]]

implement a genetic algorithm to generate haikus drawn from a dictionary annotated with syllable counts, then pay people to read and rate them as the fitness function [mechanical turk would help]. Over time your program should evolve some good ones.

EDIT:

a GA you need 
evolves at CPU speed 
if fitness you heed

blocks|key|4349812|text|“用十七个音节来表达自己的情绪是很困难的……”(伟大的John+Cooper+Clarke查看我最喜欢的Beasley+Street之一)|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|4349813|对于一台计算机来说，难度有多大？逻辑不知道情绪:)|4349814|entityMap|0|LINK|mutability|MUTABLE|url|http://www.johncooperclarke.com/Pages/poemlist.htm|1|http://www.johncooperclarke.com/Pages/beasley.htm^0|R|I|0|1G|E|1|0|0^^$0|@$1|2|3|4|5|6|7|P|8|@]|9|@$A|Q|B|R|1|S]|$A|T|B|U|1|V]]|C|$]]|$1|D|3|E|5|6|7|W|8|@]|9|@]|C|$]]|$1|F|3|-4|5|6|7|X|8|@]|9|@]|C|$]]]|G|$H|$5|I|J|K|C|$L|M]]|N|$5|I|J|K|C|$L|O]]]]

"To convey one's mood in seventeen Syllables is very diffic . . ."
(The great <a href="http://www.johncooperclarke.com/Pages/poemlist.htm" rel="nofollow noreferrer">John Cooper Clarke</a> Check out <a href="http://www.johncooperclarke.com/Pages/beasley.htm" rel="nofollow noreferrer">Beasley Street</a>, one of my favourites)

How much more diffic for a computer? Logic knows no moods :)

blocks|key|1010106|text|为了使字典具有可读性，请将字典分成名词、动词、形容词，并进行音节计数。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1010107|提供表单的一些模板：|1010108|名词“s”|1010109|动词a(n)形容词|1010110|形容词|1010111|把你的字典改成漂亮的单词。|1010112|entityMap^0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|N|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|O|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|P|8|@]|9|@]|A|$]]|$1|F|3|G|5|6|7|Q|8|@]|9|@]|A|$]]|$1|H|3|I|5|6|7|R|8|@]|9|@]|A|$]]|$1|J|3|K|5|6|7|S|8|@]|9|@]|A|$]]|$1|L|3|-4|5|6|7|T|8|@]|9|@]|A|$]]]|M|$]]

To make it readable, separate the dictionary into Nouns, Verbs, Adjectives, with syllable count.

Come up with some templates of the form:

[Noun] [Verb]"s"

[Verb] a(n) [Adjective] [Noun]

[adjective] [noun]

and trim your dictionaries to the beautiful words.

blocks|key|285563|text|你的程序必须理解|type|unstyled|depth|inlineStyleRanges|entityRanges|data|285564|元标量和图像|285565|要有创意。|285566|entityMap^0|0|0|0^^$0|@$1|2|3|4|5|6|7|H|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|I|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|J|8|@]|9|@]|A|$]]|$1|F|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|G|$]]

Your program must grok 
Metaphores and imagery 
And be creative.

blocks|key|1009901|text|我会查找语法编程和语言学，并尝试找到语法结构的库。从那里开始，添加单词计数和音节计数约束应该是一个简单的步骤。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1009902|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|D|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|E|8|@]|9|@]|A|$]]]|C|$]]

I would look up syntactical programming and linguistic and try to find libraries for grammatical structure. From there it should be a simple step to add the word count and syllable count constraints.

blocks|key|1010075|text|这里的一些人建议使用字典，并使用马尔可夫链生成单词序列。这似乎是一个理论上可行的解决方案，特别是如果您使用高阶马尔可夫链(而不是双或三元组)。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1010076|但我认为，在实践中，如果你能收集现有的haikus数据库，并有选择地更改其中的单个单词(例如，将一个给定的单词更改为另一个语义相关的单词)，效果会更好。现有的haiku赋予了你某种结构和内聚力，你只需要(ex-)改变它们中的一些小部分，就可以创建一个新的haiku(旧haiku的变体)。|1010077|当然，使用这种方法，它们不会是全新的haikus，但至少对读者来说，它们会有点令人愉快。|1010078|entityMap^0|0|0|0^^$0|@$1|2|3|4|5|6|7|H|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|I|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|J|8|@]|9|@]|A|$]]|$1|F|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|G|$]]

Some people here suggested using a dictionary and generating word sequences using a Markov Chain. That seems like a theoretically viable solution, especially if you use a high-order Markov Chain (not bi- or trigrams). 

But I think in practice it would work better if you could collect a database of existing haikus and selectively change single words in them (e.g., change a given word to another, semantically related word). The existing haikus give you some kind of structure and cohesion, and you just need to (ex-)change little parts in them in order to create a new haiku (a variation on the old one). 

Of course they won't be completely new haikus with this method, but at least they will be somewhat enjoyable for the readers.

blocks|key|4349940|text|按照关系顺序解析现有的haikus，比如在yy+n次之后使用的单词xx。因此，在创建时，xx出现在yy之后的可能性将是(n+/yy之后使用的所有单词的总数)。通过这种方式，它将被选择性地随机化，并且仍然可以是有效的haiku。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4349941|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|D|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|E|8|@]|9|@]|A|$]]]|C|$]]

Parse existing haikus in a relational order, like word xx used after yy n times. 
So when creating, possibility of xx coming after yy will be (n / sum of count of all words used after yy). This way it will be selectively randomized and can still be a valid haiku.

blocks|key|285492|text|编写你的程序来生成日语的Haiku。测量你的音节数会容易得多，因为你忠于诗歌的原始语言。如果你对这个项目有灵活性，为什么不制作原版日语-然后在旁边显示英文逐字直译。至少可以说它看起来很神秘。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|285493|无论如何，只是对这个问题有不同的看法。|285494|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|F|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|G|8|@]|9|@]|A|$]]|$1|D|3|-4|5|6|7|H|8|@]|9|@]|A|$]]]|E|$]]

Write your program to generate Haiku's in Japanese. It will be far easier to measure your syllable count, pluse you are staying faithful to the original language of the poetry. If you have flexibility with the project, why not make the original Japanese - then show the English word by word literal translation by its side. It will look mysterious to say the least.

Anyways, just a different take on the problem.

blocks|key|1010282|text|马尔可夫序列|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1010283|音节数据库|1010284|三行python|1010285|entityMap^0|0|0|0^^$0|@$1|2|3|4|5|6|7|H|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|I|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|J|8|@]|9|@]|A|$]]|$1|F|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|G|$]]

Markov Sequences 
A syllabic Database 
Three lines of python

blocks|key|1009849|text|我会从某种类型的字典文件开始，该文件包含其中每个单词的音节计数。然后从加起来达到所需音节/行的单词中挑选单词|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1009850|至于让它变得有诗意，而不仅仅是随机的单词，我不知道。|1009851|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|F|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|G|8|@]|9|@]|A|$]]|$1|D|3|-4|5|6|7|H|8|@]|9|@]|A|$]]]|E|$]]

I'd start with some kind of dictionary file that contains a syllable count of each word in it. Then pick words from that add up to the required syllables/line

As to making it poetry, and not just random words, I have no idea.

blocks|key|1005201|text|除了使用Ian的音节计数思想外，您还可以根据词性对单词进行分类并生成短语。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1005202|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|D|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|E|8|@]|9|@]|A|$]]]|C|$]]

You could, in addition to using Ian's idea of syllable counts, also categorize the words by part of speech and generate phrases.

blocks|key|3502115|text|从故事的语义sude出发，使用采样和傅立叶变换。选择一些详细描述中的重要部分，让读者用自己的想象力来填补空白|type|unstyled|depth|inlineStyleRanges|entityRanges|data|3502116|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|D|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|E|8|@]|9|@]|A|$]]]|C|$]]

From the semantic sude of the story use sampling and fourier transformation. Pick significant parts of some detailed description reduced in single words and leave to a reader to fill in gaps with her own imagination

blocks|key|4350184|text|让计算机输出高质量的haiku的算法是这样工作的：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4350185|设置阶段|4350186|loop:
++find+the+email+address+of+a+world-renowned+writer+of+haiku
++confirm+that+this+person+is+willing+to+generate+haiku+on+demand
until+sucker%5EH%5EH%5EH%5EH%5EH%5EHwriter+is+found|code-block|syntax|javascript|4350187|执行阶段|4350188|loop:
++wait+for+a+haiku+request
++when+a+haiku+request+is+received,+email+the+previously-stored+master+and+ask+for+a+haiku
++wait+for+the+haiku+to+return+by+reply
++output+haiku|4350189|当然，可以在这个基础架构上进行各种增强。例如，可以将设置阶段扩展到设置一个haiku专家池。执行阶段可以用来在空闲时间生成haiku，并根据未来的需求对它们进行缓存。这种调整的细节留给学生作为练习。|4350190|entityMap^0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|Q|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|R|8|@]|9|@]|A|$]]|$1|D|3|E|5|F|7|S|8|@]|9|@]|A|$G|H]]|$1|I|3|J|5|6|7|T|8|@]|9|@]|A|$]]|$1|K|3|L|5|F|7|U|8|@]|9|@]|A|$G|H]]|$1|M|3|N|5|6|7|V|8|@]|9|@]|A|$]]|$1|O|3|-4|5|6|7|W|8|@]|9|@]|A|$]]]|P|$]]

The algorithm for having a computer output high quality haiku works something like this:

<h2>Setup Phase</h2>

<pre><code>loop:
 find the email address of a world-renowned writer of haiku
 confirm that this person is willing to generate haiku on demand
until sucker^H^H^H^H^H^Hwriter is found
</code></pre>

<h2>Execution Phase</h2>

<pre><code>loop:
 wait for a haiku request
 when a haiku request is received, email the previously-stored master and ask for a haiku
 wait for the haiku to return by reply
 output haiku
</code></pre>

There are, of course, various enhancements which can be made upon this fundamental architecture. For example the setup phase can be extended to set up a pool of haiku experts. The execution phase can be used to generate haiku during idle times and cache them against future demand. The specifics of such tweaking are left as an exercise for the student.

blocks|key|4350150|text|我喜欢这个问题。它非常有想象力。请在下面回答。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4350151|4350152|许多人建议使用马尔可夫链，但我真的不认为这是可能的。你需要智能地知道音节是否是音素，然后你必须知道音节在哪里结束。|4350153|如果你曾经这样做过，我会很惊讶的。|4350154|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|J|8|@]|9|@]|A|$]]|$1|C|3|D|5|6|7|K|8|@]|9|@]|A|$]]|$1|E|3|F|5|6|7|L|8|@]|9|@]|A|$]]|$1|G|3|-4|5|6|7|M|8|@]|9|@]|A|$]]]|H|$]]

I love this question. 
It is very imaginative.
Answer Below.

<hr>

Many people have suggested Markov chains, but I really don't think it would be possible. You need to know intelligently whether the syllable is a PHONEMES then you have to know where the syllable ends. 

If you ever did this I would be amazed.

Computer Haiku 
How would you write a program 
To make them for you

How would you write a program to generate Haiku?

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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