First feasability test: dictionary morphing

The first test carried out to transform the dictionary (in the extended sense) based on the French-Corsican pair, into a dictionary related to the Italian-Gallurian pair, shows that it is feasible. The result – of an acceptable but perfectible quality – is obtained in 21 minutes (with 16 GO RAM & Intel core i7-8550U CPU). We start with a multi-lingual dictionary based on French entries, and the final result is an Italian-Gallurese dictionary.

Posted in blog | Tagged , , , | Comments Off on First feasability test: dictionary morphing

Translation from Italian to Gallurese

Our new project will be to try to implement the translation from Italian into Gallurese. For this is an essential pair for the Gallurese language, which is a priority. The major difficulty in doing this is:
– on the one hand, to (automatically) transform the dictionary (in the extended sense) based on the French-Corsican pair, into a dictionary related to the Italian-Gallurese pair
– on the other hand, to implement automatically (without having to rewrite them entirely) the other modules, and in particular the one based on grammatical disambiguation.

The stakes here seem high. It is a question of transforming a system that can translate one pair of languages (i.e. French into Corsican) into an eco-system that can translate several pairs of languages (the target language of which being an endangered language).

Posted in blog | Tagged , , , | Comments Off on Translation from Italian to Gallurese

Adjective modifiers again

We will consider again a category of words such as ‘very’, when they precede an adjective. Traditionally, this category is termed ‘adverbs’ or ‘adverbs of degree’, but we prefer ‘adjective modifier’, because (i) analytically, they change the meaning of an adjective and (ii) synthetically, an adjective modifier followed by an adjective is still an adjective. A more complete list is: almost, absolutely, badly, barely, completely, decidedly, deeply, enormously, entirely, extremely, fairly, fully, greatly, hardly, highly, how, incredibly, intensely, less, most, much, nearly, perfectly, positively, practically, pretty, purely, quite, rather, really, scarcely, simply, somewhat, strongly, terribly, thoroughly, totally, utterly, very, virtually, well.

If we look at sentences such as: il est bien content (he is very happy, hè beddu cuntenti), ils étaient bien contents (they were very happy, erani beddi cuntenti), elle serait bien contente (she would be very happy, saria bedda cuntenti), elles sont bien contentes (they are very happy, sò beddi cuntenti), we can see that the modifier of the adjective ‘bien’ is rendered as very in English and in Corsican as:

  • bellu/beddu: singular masculine
  • belli/beddi: plural masculine
  • bella/bedda: feminine singular
  • belle/beddi: feminine plural

This shows that the adjective modifier is invariable in French and English, but varies in gender and number in Corsican. Thus, in Corsican grammar, it seems appropriate to distinguish between:

  • singular masculine adjective modifier
  • plural masculine adjective modifier
  • singular feminine adjective modifier
  • plural feminine adjective modifier

On the other hand, such a distinction does not seem useful in English and French, where the category of ‘adjective modifier’ is sufficient and there is no need for further detail.

Posted in blog | Tagged , , , , , , | Comments Off on Adjective modifiers again

On ‘reflexive pronouns’

Pursuing the reflection on grammatical categories, we will examine now “reflexive pronouns”. These are:

  • me te se nous vous se (French)
  • mi ti si ci vi si (Corsican)
  • myself yourself himself/herself/itself ourselves yourselves themselves

Let us take an example:

  • je me promène, tu te promènes, il se promène, nous nous promenons, vous vous promenez, ils se promènent
  • I walk, you walk, he walks, we walk, we walk, you walk, they walk
  • spassieghju, spassieghji, spassieghja, spassiemu, spassieti, spassièghjani

These reflexive pronouns are usually associated with so-called pronominal verbs.
From our point of view, this classification as ‘pronouns’ is unsatisfactory, because they always precede a verb,1 but are placed after a personal subject pronoun, an indefinite pronoun, or a nominal group. In particular, the notion of pronoun following a pronoun is not coherent, from the point of view of our analysis, where the main criterion for typology is the position of a given grammatical type in relation to another.

Let us recall here that the idea behind this reconstruction of grammatical typology is the hypothesis that traditional classification lacks coherence and that this considerably hinders the development of natural language analysis and, at the same time, the development of machine translation modules based on the emulation of human reasoning.

This example suggests that the classic ‘reflexive pronoun’ is a word that introduces into the verb to which it refers a notion of reflexivity of action. In this sense, it is more of a specialized verb modifier. It is thus more akin to the adverb in the sense that we have defined it, i.e. a verb modifier in the broad sense. The adverb in this sense can be placed before or after the verb. On the other hand, the reflexive verb modifier as we have defined it can only be placed in French before the verb.

1 I oversimplify here, since there are also some structures like: tu t’en souviens (you remember it, ti n’inveni).

Posted in blog | Comments Off on On ‘reflexive pronouns’

Grammatical word-disambiguation again

The challenge is especially that of generalizing the grammatical word-disambiguation to several languages. Creating a module of grammatical word-disambiguation for each language appears to be a long and arduous task. This seems to be the main difficulty. But if a module specific to a given language can be generalized to several other languages, this could be an important advance in the field of rule-based machine translation (which simulates human reasoning seems to me a more appropriate term).

We can describe the problem more precisely. We have about 100 grammatical categories for a given language. We also have about 300 ambiguous grammatical types – to fix ideas – which are: e.g., adverb or preposition, singular masculine noun or singular masculine adjective, etc. The problem is to describe an algorithm to remove the ambiguity and determine the corresponding grammatical type according to the context.

Now rewriting the complete module of disambiguation by grammatical type, so that it can be used and adapted to other languages (Italian in the first place). It remains to be seen if this can be done.

Posted in blog | Tagged , , , , | Comments Off on Grammatical word-disambiguation again

First steps in gallurese language

The translator takes his first steps in translating from French into the Gallurian language. The first tests show a score of 75-80%, with many errors in grammar, spelling and vocabulary. It will be necessary to reach a score of 90% before the result can be published.

The ideal would have been the Italian-Gallurian translation, but this is not yet possible: it will be necessary to translate (i) Italian into French, then (ii) French into Gallurian.

Posted in blog | Tagged , , , , | Comments Off on First steps in gallurese language

Hinting at the Control problem

The question of choosing the best system to solve the problems posed by word disambiguation in the field of translation seems to be linked to the AGI control problem (how to avoid that an AGI finally turns out to be harmful for its creators). It seems that when we have the choice between several methods to develop an AI, it is wiser to choose the one that allows a better control of the AGI. As far as machine translation is concerned, we should thus prefer in this regard the method that emulates human reasoning, and that produces a response that can be broken down step by step into the reasoning that leads to it. This makes it possible to accurately determine the cause of an error, but also to remedy it. This problem does not only concern machine translation, but has a somewhat extended scope. For grammatical disambiguation concerns machine translation, but also the understanding of natural language, and disambiguation according to context, in the very absence of any translation.

Posted in blog | Tagged , , , | Comments Off on Hinting at the Control problem

On the implementation of grammatical disambiguation

Grammatical disambiguation – i.e. whether ‘maintenant’ is and adverb (now) or the gerundive (maintaining) of the verb ‘maintenir’ – seems to be the crucial issue for the adoption of the rule-based model or statistical model for machine translation. This problem is widespread and seems to concern all languages. For the French language, this problem of grammatical disambiguation concerns about 1 word out of 7. Effective grammatical disambiguation is difficult to implement. The advantage of adopting the statistical method for grammatical disambiguation is that the same method can be generalized and used for several languages. In the case of the rule-based model, the module of grammatical disambiguation must be rewritten for each language, which generates considerable complexity and requires a very significant development time. Therefore, a rule-based method for grammatical disambiguation that can be easily applied to several languages would be of great interest. This seems to be the main difficulty that rule-based machine translation is designed to overcome.

But if we want an artificial intelligence that not only provides an (mostly accurate) answer without being able to really explain its reasoning, but is truly able to emulate human reasoning and to justify and describe step by step the reasoning that leads to its answer, then it is worth the effort.

Posted in blog | Tagged , , , , | Comments Off on On the implementation of grammatical disambiguation

The 90% rule

The translation from French to Gallurese is in progress and currently under development. An application for Android is first planned. It will be called ‘traducidori gaddhuresu’. Currently the French-Gallurese translator is undergoing testing. It will only be published if its performance (evaluated by an open test) is above 90%. This is a rule that we apply to ourselves, and is specific to endangered languages. We consider that for them, a poor or low quality translation can be more harmful than useful.

Posted in blog | Tagged , , , , , , | Comments Off on The 90% rule

A “traducidori gaddhuresu” in preparation

After the Corsican language, the second endangered language for which we would like to develop a translator is the Gallurese language (“traducidori gaddhuresu”). As far as the ‘traducidori gaddhuresu’ is concerned, we are considering an Android application and a Windows version.

The priority pair for Gallurese is Italian-Gallurese. However, it will not be possible to make an Italian-Gallurese translator at first. It is a French-Gallurese translator that is first of all in preparation. It will therefore be necessary, at first, to translate a text from Italian into French first (especially with Deepl, which is of very good quality), and then to use the French-Gallurese translator.

Posted in blog | Comments Off on A “traducidori gaddhuresu” in preparation