Tag Archives: JLIFF

Exploring JLIFF

I have published a web application where you can submit XLIFF 2.x files and get back a JLIFF serialization as text.

JLIFF is a new XLIFF serialization format currently in working draft with the OASIS Object Model and Other Serializations Technical Committee.

The application uses my open source JliffGraphTools library.

I am working on a conversion of XLIFF 1.2 to JLIFF but as the content model is structurally different it’s tricky.

I was careful to implement it in a way that means no data is persisted. I don’t even collect any metadata about what is submitted. That way people can feel confident of about the privacy of their data.

Serverless Machine Translation

It is well known that you can produce relatively good quality machine translations by doing the following:

  • Carry out some processing on the source language.
    Such as remove text which serves no purpose in the translations (say, imperial measurements in content destined for Europe); re-order some lengthy sentences; mark the boundaries of embedded tags, etc.
  • Use custom domain trained machine translation engines.
    This is possible with several machine translation providers. If you have an amount of good quality bilingual and monolingual corpora relevant to your subject matter then you can train and build engines which will produce higher quality output than a general public domain engine.
  • Post process the raw machine translation output to correct recurrent errors.
    To improve overall fluency; replace specific terminology, etc.

We decided to implement this in a fully automated Azure Functions pipeline.

NOTE: Some MT providers have this capability built into their services but we wanted the centralized flexibility to control the pre- and post-editing rules and to be able to mix and match which MT providers we get the translations from.

The pipeline consists of three functions: preedit, translate and postedit. The json payload used for inter-function communication is Jliff. Jliff is an open object graph serialization format specification being designed by an OASIS Technical Committee.

NOTE: Jliff is still in design phase but I’m impatient and it seemed like a good way to test the current snapshot of the format.

The whole thing is easily re-configured and re-deployed, and has all the advantages of an Azure consumption plan.

We can see that this pipeline would be a good candidate for durable functions so once we have time we’ll take a look at those.

Serializing and Deserializing JLIFF

I’ve been having all kinds of fun saving text (json) representations of translation units (pairs of source and target language strings), sending them from one cloud based service to another and then rebuilding the in-memory object representations from the text representation.

I know that any software engineer will be yawning about now because libraries for doing this kind of thing have existed for a long time. However, it’s been fun for me partly because I’m doing it inside the new Azure Function service, and because some of the objects have abstract relationships (interfaces and sub-classes) introducing some subtleties to getting this to work which took a lot of research to implement.

It relates to the work of the OASIS OMOS TC whose evolving schema for what has been dubbed JLIFF can be seen on GitHub.

The two parts of the object graph requiring the special handling are the array containing the Segment‘s and Ignorable‘s (which implement the ISubUnit interface in my implementation), and the array containing the text and inline markup elements of the Source and Target containers (which implement the IElement interface and subclass AbstractElement in my implementation).

When deserializing the components of these arrays each needs a class which derives from Newtonsoft.Json.JsonConverter.

namespace JliffModel
{
    using System;
    using Newtonsoft.Json;
    using Newtonsoft.Json.Linq;

    public class ISubUnitConverter : JsonConverter
    {
        public override bool CanConvert(Type objectType)
        {
            var canConvert = false;

            if (objectType.Name.Equals("ISubUnit")) canConvert = true;

            return canConvert;
        }

        public override object ReadJson(JsonReader reader, Type objectType, object existingValue, JsonSerializer serializer)
        {
            var jobject = JObject.Load(reader);

            object resolvedType = null;

            if (jobject["type"].Value().Equals("segment")) resolvedType = new Segment();

            serializer.Populate(jobject.CreateReader(), resolvedType);

            return resolvedType;
        }

        public override void WriteJson(JsonWriter writer, object value, JsonSerializer serializer)
        {
            writer.WriteValue(value.ToString());
        }
    }
}

Then the classes derived from JsonConverter are passed into the Deserialize method.

    Fragment modelin = JsonConvert.DeserializeObject<Fragment>(output,
        new ISubUnitConverter(),
        new IElementConverter());