[Corpora-List] Parallel corpora and word alignment, WAS: American and British English spelling converter

[Dr Hatch]

Dear Merle

I seem to remember that some months ago Fiona Barker at UCLE said (on the
list or in an email) that some at UCLES were compiling a corpus of L2
English learners. I have been doing the same, but in a very amateurish way
­lacking the resources of CU.

I'm not sure about the etiquette of giving out a person's email address, but
perhaps Fiona will respond to your posting, anyway.

Many of us would be very interested in an L2 English learners corpus,
particularly if the learners' L1 was 'knowable'.

David 


On 11/11/06 12:09 AM, "Merle Tenney" <merlet at microsoft.com> wrote:

> Ramesh,
>  
> Lots of people are working with parallel corpora in two or more languages. 
> Honestly, I don¹t know of any effort to acquire parallel corpora of two or
> more varieties of English, French, Portuguese, etc.  I should think that
> sources for such corpora must exist, though not nearly to the extent that they
> exist for texts in different languages.  Another variant on the parallel
> corpus theme is papers written by English language learners and the corrected
> versions with interference problems removed.  Again, it is not hard to imagine
> that such sources exist, but I cannot provide a reference for either sort of
> same-language corpus.  Can someone point Ramesh and me in the right direction?
>  
> Merle
>  
> 
> From: Ramesh Krishnamurthy [mailto:r.krishnamurthy at aston.ac.uk]
> Sent: Friday, November 10, 2006 6:46 AM
> To: Merle Tenney; Mark P. Line; CORPORA at UIB.NO
> Subject: Re: [Corpora-List] Parallel corpora and word alignment, WAS: American
> and British English spelling converter
>  
> Hi Merle
> I must admit I hadn't been thinking of "parallel" corpora along such
> strict-definition lines.
> 
> So who is creating large amounts of 'parallel' data (in the
> technical/translation sense)
> for British English and American English? I wouldn't have thought there was a
> very large 
> market....?
> 
> Noah Smith mentioned Harry Potter, and I must admit I'm quite surprised to
> discover 
> that publishers are making such changes as
> 
> 
>    They had drawn for the house cup
>    They had tied for the house cup
> Perhaps because it's "children's" literature? Or at least read by many
> children, 
> who may not be willing/able to cross varietal boundaries with total comfort.
> 
> But when I read a novel by an American author, I accept that it's part of my
> role as reader to
> take on board any varietal differences as part of the context. I can't imagine
> anyone wanting
> to translate it into British English for my benefit, and I suspect I would
> hate to read the resulting
> text...
> 
> Best
> Ramesh
> 
> 
> At 18:53 09/11/2006, Merle Tenney wrote:
> 
> 
> Ramesh Krishnamurthy wrote:
>> > 
>> > ...and there is no obvious parallel corpus of Br-Am Eng to consult...
>> > Do you know of one by any chance...
>> > 
>> > And Mark P. Line responded:
>> > 
>> >Why would it have to be a *parallel* corpus?
>  
> In a word, alignment.  The formative work in parallel corpora has come from
> the machine translation crowd, especially the statistical machine researchers.
> The primary purpose of having a parallel corpus is to align translationally
> equivalent documents in two languages, first at the sentence level, then at
> the word and phrase level, in order to establish word and phrase equivalences.
> A secondary purpose, deriving from the sentence-level alignment, is to produce
> source and target sentence pairs to prime the pump for translation memory
> systems.
>  
> Like you, I have wondered why you couldn't study two text corpora of similar
> but not equivalent texts and compare them in their totality.  Of course you
> can, but is there any way in this scenario to come up with meaningful
> term-level comparisons, as good as you can get with parallel corpora?  I can
> see two ways you might proceed:
>  
> The first method largely begs the question of term equivalence.  You begin
> with a set of known related words and you compare their frequencies and
> distributions.  So if you are studying language models, you compare sheer,
> complete, and utter as a group.  If you are studying dialect differences, you
> study diaper and nappy or bonnet and hood (clothing and automotive).  If you
> are studying translation equivalence in English and Spanish, you study flag,
> banner, standard, pendant alongside bandera, estandarte, pabellón (and flag,
> flagstone vs. losa, lancha; flag, fail, languish, weaken vs. flaquear,
> debilitarse, languidecer; etc.).  The point is, you already have your
> comparable sets going in, and you study their usage across a broad corpus.
> One problem here is that you need to have a strong word sense disambiguation
> component or you need to work with a word sense-tagged corpus to deal with
> homophonous and polysemous terms like sheer, bonnet, flat, and flag, so you
> still have some hard work left even if you start with the related word groups.
>  
> The second method does not begin, a priori, with sets of related words. In
> fact, generating synonyms, dialectal variants, and translation equivalents is
> one of its more interesting challenges.  Detailed lexical, collocational, and
> syntactic characterizations is another.  Again, this is much easier to do if
> you are working with parallel corpora.  If you are dealing with large,
> nonparallel texts, this is a real challenge.  Other than inflected and
> lemmatized word forms, there are a few more hooks that can be applied,
> including POS tagging and WSD.  Even if both of these technologies perform
> well, however, that is still not enough to get you to the quality of data that
> you get with parallel corpora.
>  
> Mark, if you can figure out a way to combine the quality and quantity of data
> from a very large corpus with the alignment and equivalence power of a
> parallel corpus without actually having a parallel corpus, I will personally
> nominate you for the Nobel Prize in Corpus Linguistics.  J
>  
> Merle
>  
> PS and Shameless Microsoft Plug:  In the last paragraph, I accidentally typed
> ³figure out a why to combine² and I got the blue squiggle from Word 2007,
> which was released to manufacturing on Monday of this week.  It suggested way,
> and of course I took the suggestion.  I am amazed at the number of mistakes
> that the contextual speller has caught in my writing since I started using it.
> I recommend the new version of Word and Office for this feature alone.  J
> Ramesh Krishnamurthy
> 
> Lecturer in English Studies, School of Languages and Social Sciences, Aston
> University, Birmingham B4 7ET, UK
> [Room NX08, North Wing of Main Building] ; Tel: +44 (0)121-204-3812 ; Fax: +44
> (0)121-204-3766
> http://www.aston.ac.uk/lss/staff/krishnamurthyr.jsp
> 
>  <http://www.aston.ac.uk/lss/staff/krishnamurthyr.jsp> Project Leader, ACORN
> (Aston Corpus Network): http://corpus.aston.ac.uk/
> 


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