什么是语言？

目前为止，我们见过了一些处理单词、句子和文档等符号序列的方法：

• 语言模型
• 隐马尔可夫模型
• 循环神经网络

但是，这些模型都没有涉及到语言的本质，因为它们可以用于处理任何符号序列，而不仅限于单词、句子等。

Formal Language Theory 形式语言理论

形式语言理论 (Formal Language Theory) 为我们提供了一种定义语言的框架，它是一种数学框架。

• Studies classes of languages and their computational properties 研究语言的类及其计算性质

• Language: set of strings 一种语言 = 字符串 (strings) 的集合

• String: sequence of elements from a finite alphabet 一个字符串 = 来自一个有限 字母集 (alphabet) 的 元素 (element) 所组成的序列

  • 字母集可以视为 词典 (vocabulary)
  • 元素可以视为 单词 (words)

动机

形式语言理论研究的是语言的 类别 (classes) 和它们的计算特性。这门课中，我们将主要介绍以下两种形式语言：

* 正则语言 (Regular Language)
* 上下文无关语言 (Context Free Language)

这两种语言构成了形式语言理论中的前两个类别，之后还有更复杂的 上下文敏感语言 (Context Sensitive Language) 等，但是这门课中我们不会对其进行过多展开。

主要目的是为了解决 从属问题 (membership problem)：一个字符串是否属于某种语言。

那么，我们应该怎样做呢？我们可以定义该语言的 语法 (grammar)，然后检查该字符串是否符合该语法规则。

例子

• E.g. of language:
  • Binary strings that start with 0 and end with 1: 二进制串（Binary strings）以 0 开头，以 1 结尾
    • {01, 001, 011, 0001, ....} belongs to this language
    • {1, 0, 00, 11, 100, ....} does not belong to this language
  • Even-length sequences from alphabet {a, b}: 来自字母集 {a, b} 的偶数长度的序列
    • {aa, ab, ba, bb, aaaa, ....} belongs to this language
    • {aaa, aba, bbb, ....} does not belong to this language
  • 以 wh- 类型的单词作为开头，问号 ？结尾的英文句子
    • {what?, where my pants?, …} belongs to this language

除了从属问题之外的问题

• 从属问题（Membership）
  • 某个字符串是否属于某种语言？是/否
• Beyond membership problem:
  • Scoring: 记分（Scoring）
    • Graded membership: How acceptable is a string
    • 具有记分等级的从属关系
    • 某个字符串在多大程度上可以被接受？（语言模型）
  • Transduction: 转导（Transduction）
    • Translate one string into another
    • 将一个字符串转变为另一个字符串（词干提取 stemming）

Regular Language

Regular Languages 正则语言

• The simplest class of languages 正则语言（Regular language）：语言中最简单的类别。

• Any regular expression is a regular language 任何 正则表达式（regular expression）都是一种正则语言。

  • Describes what strings are part of the language. E.g. 0(0|1)*1 描述了什么样的字符串是该语言的一部分

• Formally, a regular expression includes the following operations/definitions: 正式地，一个正则表达式包含以下运算：

  • Symbol drawn from alphabet Σ 从字母集中抽样得到的符号： Σ
  • Empty string ε 空字符串： ε
  • Concatenation of two regular expression 两个正则表达式的连接
    RS
  • Alternation of two regular expressions 两个正则表达式的交替RIS
  • Kleene star for 0 or more repeats 星号表示出现 0 次或者重复多次 R*
  • Parenthesis () to define scope of operations 圆括号定义运算的有效范围

• E.g.

  • Binary strings that start with 0 and ends with 1: 0(0|1)*1
  • Even-length sequences from alphabet {a, b}: ((aa)|(ab)|(ba)|(bb))*
  • English sentences that start with wh-word and end in ?: ((what)|(where)|(why)|(which)|(whose)|(whom))Σ*?

• Properties of Regular Languages:

  • Closure: If we take regular languages L1 and L2 and merge them, is the resulting language regular?
  • Regular languages are closed under these conditions/operations:
    • Concatenation and union
    • Intersection: strings that are valid in both L1 and L2
    • Negation: strings that are not in L
  • Extremely versatile. Can have regular languages for different properties of language, and use the together.

Finite State Acceptor

Finite State Acceptor 正则语言的性质

• Regular expression defines a regular language. But it does not give an algorithm to check whether a string belongs to a language 封闭（Closure）：如果我们对正则语言 L1 和 L2 进行合并，得到的结果仍然是正则语言吗？如果是，那么我们将该运算称为 封闭运算（closed operation）。

• Finite state acceptor (FSA) describes the computation involved for membership checking 在以下运算中，正则语言是封闭的：
  连接（concatenation）和 求并（union）：来自封闭的定义。
  求交（intersection）：在正则语言 L1 和 L2 中都合法的字符串。
  求反（negation）：不在正则语言 L 中的字符串。

• FSA consists:

  • Alphabet of input symbols Σ
  • Set of states Q
  • Start state q0 ∈ Q
  • Final states F ⊆ Q
  • Transition function: symbol and state -> next state

• Accepts strings if there is a path from q0 to a final state with transitions matching each symbol

  • Djisktra’s shortest-path algorithm, complexity O(V logV + E)

• E.g.:

  • Input alphabet : {a, b}
  • States: {q0, q1}
  • Start, final states: q0, {q1}
  • Transition function: {(q0, a) -> q0, (q0, b)-> q1, (q1, b) -> q1}
  • Regular expression defined by this FSA: a*bb*

Derivational Morphology

• Use of affixes to change word to another grammatical category

• E.g.:

  • grace -> graceful -> gracefully
  • grace -> disgrace -> disgracefully
  • allure -> alluring -> alluringly
  • allure -> *allureful
  • allure -> *disallure

• FSA for Morphology:

  • Want to accept valid forms (grace -> graceful)
  • Reject invalid ones (allure -> *allureful)
  • generalize to other words

  

Weighted FSA

• Some words are more plausible than others:

  • fishful vs. disgracelyful
  • musicky vs. writey

• Weighted FSA: graded measure of acceptability:

  • Start state weight function: λ: Q -> R
  • Final state weight function: ρ: Q -> R
  • Transition function: δ:(Q, Σ, Q) -> R

• Shortest-Path:

  • Total score of a path:

  

  • Use shortest-path algorithm to find π with minimum cost. Complexity: O(V logV + E)

Finite State Transducer

Finite State Transducer (FST)

• Often do not want to just accept or score strings. But want to translate them into another string.

• FST add string output capability to FSA

  • Includes an output alphabet
  • Transitions now take input symbol and emit output symbol (Q, Σ, &Sigma, Q)

• Can be weighted (WFST) : Graded scores for transition

• E.g. Edit distance as WFST: distance to transform one string to another

  

FST for Inflectional Morphology

• Verb inflection in Spanish must match the subject in person and number
• Goal of morphological analysis:
  • canto -> cantar + VERB + present + 1P + singular

  

Non-Regular Languages

• Arithmetic expressions with balanced parentheses
  • (a + (b * (c / d)))
  • Can have arbitrarily many opening parentheses
  • Need to remember how many open parentheses to produce the same number of closed parentheses
  • Can not be done with finite number of states

Center Embedding

• Center embedding of relative clauses

  • The cat loves Mozart
  • The cat the dog chased loves Mozart
  • The cat the dog the rat bit chased loves Mozart
  • The cat the dog the rat the elephant admired bit chased loves Mozart

• Need to remember the n subject nouns, to ensure n verbs follow

• Requires context-free grammar