Language Model Grammar Conversion Wesley Holland, Julie Baca, Dhruva Duncan, Joseph Picone Center...

Language Model Grammar Conversion

Wesley Holland, Julie Baca, Dhruva Duncan, Joseph PiconeCenter for Advanced Vehicular Systems

Mississippi State University

XML ABNF

BNFIHD

BNF JSGF

Page 2 of 10Language Model Grammar Conversion

Speech Recognition

• Acoustic Model• Maps audio data to words or phonemes

• Language Model• Specifies order in which a sequence of words or phonemes is likely to

occur

• Described using grammar

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Grammar Specifications

• Backus-Naur Form (BNF)

• Augmented BNF (ABNF)

• JSpeech Grammar Format (JSGF)

• Speech Recognition Grammar Specification (SRGS)

• ISIP Hierarchical Digraph (IHD)

<A>::=ab* <A>=a(b)*;

a<item repeat=“0-”> b</item>

BNF<A>::=aB<B>::=bB<B>::=ε

ABNF JSGF

XML-SRGS IHD

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Conversion Design

• Goals• JSGF ↔ IHD

• XML-SRGS ↔ IHD

• Determination of equivalence

• Grammar minimization

• Final Architecture

XML

JSGF

ABNF BNF IHD

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JSGF/XML-SRGS → ABNF

• JSGF → ABNF• Trivial

• Similar in syntax and structure to ABNF

• XML-SRGS → ABNF• Harder than JSGF

• Different in syntax and structure from ABNF

• Requires enumeration of certain repeat attributes

<S>::=(ab)|(abab)

XML-SRGS<item repeat=‘1-2’> a b</item>

ABNF

<S>::=abab(ab)*

<item repeat=‘2-’> a b</item>

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JSGF/XML-SRGS → ABNF

• XML-SRGS → ABNF (continued)• Different weighting mechanisms (weight and repeat-prob attributes)

a<item repeat=“0-” repeat-prob=“.45”> b</item><one-of> <item weight=“.4”>c</item> <item weight=“.6”>d</item></one-of>

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ABNF → BNF

• Normalized BNF• Consists of rules of the following formats:

•(RULE_NAME)::=(TERMINAL),(NON_TERMINAL)

•(RULE_NAME)::=(NON_TERMINAL)

•(RULE_NAME)::=ε

ABNF

BNF

1. Break rule into multiple rules at each top-level alternation. Recurse on each rule.

2. For each concatenation, Kleene star, or Kleene plus, extract a set of left symbols and a set of right symbols.

3. For n left symbols and m right symbols, create n x m connecting rules.

• ABNF → BNF• Complicated

• Accomplished using a recursive algorithm that extracts sets of normalized BNF rules from a set of ABNF rules

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BNF ↔ IHD

• BNF ↔ IHD• Each arc translates to a normalized BNF

• Terminals correspond to nodes; concatenations correspond to arcs

RS→R0 R3→C,R3RS→R1 R3→C,RTR0→A,R3 RT→εR1→B,R3

BNFNodes1: A2: B3: C

Arcs(S,1) (2,3)(S,2) (3,3)(1,3) (3,T)

IHD

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BNF → JSGF/XML-SRGS

• BNF → JSGF/XML-SRGS• Rule-by-rule

• Trivial

<A>=aB;<B>=b*;

<rule id=“a”> a <ruleref uri=“#b”/></rule>

<rule id=“b”> <one-of> <item> b <ruleref uri=“#b”/> </item> <item> <ruleref special= “NULL”/> </item> </one-of></rule>

BNF<A>::=aB<B>::=bB<B>::=ε

JSGF

XML-SRGS

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Software Tools

• ISIP Network Converter• Console tool to perform conversions to and from arbitrary grammar

formats

• ISIP Network Builder• Java-based graphical tool to design grammars as finite state machines

• Can exports grammars to JSGF, XML-SRGS, ABNF, BNF, and IHD

• ISIP Language Model Tester• Console tool for testing of grammars

• Can generate valid sentences in a given grammar

• Can parse sentences and determine if accepted by a given grammar.

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Minimization

• Minimization• Happens in BNF

• Iterate over rule set, merging redundant rules

• Rules can be merged if the non terminal of both rules reference the same terminal

• Example: