Elasticsearch：language ingest processor - 7.6

In my previous article " elasticsearch: Ingest Language Processor ." In that article, we use a plug-in community to complete this work. In Elastic Stack release 7.6, we are pleased to tell you: in Elastic Stack, we integrated a speech recognition processor.

 

Hands

First of all, we need to install the latest release of Elastic Stack 7.6. We enter the following command in Kibana in:

PUT _ingest/pipeline/my-pipeline-id
{
  "description": "describe pipeline",
  "processors": [
    {
      "inference": {
        "model_id": "lang_ident_model_1",
        "inference_config": {
          "classification": {
            "num_top_classes": 1
          }
        },
        "field_mappings": {}
      }
    }
  ]
}

In the above we create a pipeline called my-pipeline-id's. So when we put the document into Elasticsearch, we can refer to this pipeline:
 

POST test/_doc/1?pipeline=my-pipeline-id
{
  "text": "我爱北京天安门"
}

In the above we have " I Love Beijing Tiananmen " is written to Elasticsearch in. We can check the information written by the following command:

GET test/_doc/1/

We can see a response as follows:

{
  "_index" : "test",
  "_type" : "_doc",
  "_id" : "1",
  "_version" : 2,
  "_seq_no" : 1,
  "_primary_term" : 1,
  "found" : true,
  "_source" : {
    "text" : "我爱北京天安门",
    "ml" : {
      "inference" : {
        "top_classes" : [
          {
            "class_name" : "zh",
            "class_probability" : 0.9999770918986735,
            "class_score" : 0.9999770918986735
          }
        ],
        "predicted_value" : "zh",
        "model_id" : "lang_ident_model_1"
      }
    }
  }
}

In the above, we can see a field called ml.inference.predicated_value, it shows the language zh, is Chinese.

Similarly, we can do an experiment to other languages, such as Japanese:

POST test/_doc/2?pipeline=my-pipeline-id
{
  "text": "これはフリーテキストです。"
}

So let's check the document input by the following command:

GET test/_doc/2/

Returned results above are:

{
  "_index" : "test",
  "_type" : "_doc",
  "_id" : "2",
  "_version" : 2,
  "_seq_no" : 3,
  "_primary_term" : 1,
  "found" : true,
  "_source" : {
    "text" : "これはフリーテキストです。",
    "ml" : {
      "inference" : {
        "top_classes" : [
          {
            "class_name" : "ja",
            "class_probability" : 0.999997979528696,
            "class_score" : 0.999997979528696
          }
        ],
        "predicted_value" : "ja",
        "model_id" : "lang_ident_model_1"
      }
    }
  }
}

Shown in the above ml.inference.predicted_value is "ja", which is Japanese.

If we want to use _simulate pipeline to test, then we can use the following command:

POST _ingest/pipeline/_simulate
{
  "pipeline": {
    "processors": [
      {
        "inference": {
          "model_id": "lang_ident_model_1",
          "inference_config": {
            "classification": {
              "num_top_classes": 1
            }
          },
          "field_mappings": {
          }
        }
      }
    ]
  },
  "docs": [
    {"_source": {"text": "this is some free text."}},
    {"_source": {"text": "c'est du texte libre."}},
    {"_source": {"text": "Dies ist ein Freitext."}},
    {"_source": {"text": "これはフリーテキストです。"}},
    {"_source": {"text": "یہ کچھ مفت متن ہے۔"}},
    {"_source": {"text": "我爱北京天安门"}}
    ]
}

The results show that:

{
  "docs" : [
    {
      "doc" : {
        "_index" : "_index",
        "_type" : "_doc",
        "_id" : "_id",
        "_source" : {
          "text" : "this is some free text.",
          "ml" : {
            "inference" : {
              "top_classes" : [
                {
                  "class_name" : "en",
                  "class_probability" : 0.9999832919481261,
                  "class_score" : 0.9999832919481261
                }
              ],
              "predicted_value" : "en",
              "model_id" : "lang_ident_model_1"
            }
          }
        },
        "_ingest" : {
          "timestamp" : "2020-03-04T05:51:26.380985Z"
        }
      }
    },
    {
      "doc" : {
        "_index" : "_index",
        "_type" : "_doc",
        "_id" : "_id",
        "_source" : {
          "text" : "c'est du texte libre.",
          "ml" : {
            "inference" : {
              "top_classes" : [
                {
                  "class_name" : "fr",
                  "class_probability" : 0.996991483545992,
                  "class_score" : 0.996991483545992
                }
              ],
              "predicted_value" : "fr",
              "model_id" : "lang_ident_model_1"
            }
          }
        },
        "_ingest" : {
          "timestamp" : "2020-03-04T05:51:26.380988Z"
        }
      }
    },
    {
      "doc" : {
        "_index" : "_index",
        "_type" : "_doc",
        "_id" : "_id",
        "_source" : {
          "text" : "Dies ist ein Freitext.",
          "ml" : {
            "inference" : {
              "top_classes" : [
                {
                  "class_name" : "de",
                  "class_probability" : 0.9999995801281829,
                  "class_score" : 0.9999995801281829
                }
              ],
              "predicted_value" : "de",
              "model_id" : "lang_ident_model_1"
            }
          }
        },
        "_ingest" : {
          "timestamp" : "2020-03-04T05:51:26.38099Z"
        }
      }
    },
    {
      "doc" : {
        "_index" : "_index",
        "_type" : "_doc",
        "_id" : "_id",
        "_source" : {
          "text" : "これはフリーテキストです。",
          "ml" : {
            "inference" : {
              "top_classes" : [
                {
                  "class_name" : "ja",
                  "class_probability" : 0.999997979528696,
                  "class_score" : 0.999997979528696
                }
              ],
              "predicted_value" : "ja",
              "model_id" : "lang_ident_model_1"
            }
          }
        },
        "_ingest" : {
          "timestamp" : "2020-03-04T05:51:26.380992Z"
        }
      }
    },
    {
      "doc" : {
        "_index" : "_index",
        "_type" : "_doc",
        "_id" : "_id",
        "_source" : {
          "text" : "یہ کچھ مفت متن ہے۔",
          "ml" : {
            "inference" : {
              "top_classes" : [
                {
                  "class_name" : "ur",
                  "class_probability" : 0.9999762917090316,
                  "class_score" : 0.9999762917090316
                }
              ],
              "predicted_value" : "ur",
              "model_id" : "lang_ident_model_1"
            }
          }
        },
        "_ingest" : {
          "timestamp" : "2020-03-04T05:51:26.380994Z"
        }
      }
    },
    {
      "doc" : {
        "_index" : "_index",
        "_type" : "_doc",
        "_id" : "_id",
        "_source" : {
          "text" : "我爱北京天安门",
          "ml" : {
            "inference" : {
              "top_classes" : [
                {
                  "class_name" : "zh",
                  "class_probability" : 0.9999770918986735,
                  "class_score" : 0.9999770918986735
                }
              ],
              "predicted_value" : "zh",
              "model_id" : "lang_ident_model_1"
            }
          }
        },
        "_ingest" : {
          "timestamp" : "2020-03-04T05:51:26.380995Z"
        }
      }
    }
  ]
}