Intent

The Intent Analysis model will help you capture semantics behind users' messages and assign it to the right label. It is designed to understand human conversation in the form or free text or spoken text.

modelType Configuration

Keys	Value
modelType	intent_analysis
modelConfig	Model Configuration object for intent_analysis - the intent ids to be used for intent recognition

Example Request

Curl

curl --location --request POST 'https://api.marsview.ai/cb/v1/conversation/compute' \
--header 'Content-Type: application/json' \
--header "Authorization: {{Insert Auth Token}}" \
--data-raw '{
        "txnId": "{{Insert txn ID}}",
        "enableModels":[
            {
            "modelType":"speech_to_text",
                "modelConfig":{
                    "automatic_punctuation" : true,
                    "custom_vocabulary":["Marsview", "Communication"],
                    "speaker_seperation":{
                        "num_speakers":2
                    },
                    "enableKeywords":true,
                    "enableTopics":false
                    }
            },
            {
            "modelType": "intent_analysis",
            "modelConfig": {
                "config": {
                    "intents": [
                        "intent-1c6q62hzkxim6ect-1640242740269", 
                        "intent-1c6q62hzkxim9q8o-1640242895640"
                        ]
                    }
                }
            }
        ]
}'

Python

import requests
auth_token = "replace this with your auth token"
txn_id = "Replace this with your txn id"
request_url = "https://api.marsview.ai/cb/v1/conversation/compute"


def get_intents():
  payload={
        "txnId": txn_id,
        "enableModels":[
            {
            "modelType":"speech_to_text",
                "modelConfig":{
                    "automatic_punctuation" : True,
                    "custom_vocabulary":["Marsview", "Communication"],
                    "speaker_seperation":{
                        "num_speakers":2
                    },
                    "enableKeywords":True,
                    "enableTopics":False
                }
            },
            {
            "modelType": "intent_analysis",
            "modelConfig": {
                "config": {
                    "intents": [ 
                        "intent-1c6q62hzkxim6ect-1640242740269",
                        "intent-1c6q62hzkxim9q8o-1640242895640"
                        ]
                    }
                }
            }
            ]
        }
  headers = {'authorization': '{}'.format(auth_token)}
  
  response = requests.request("POST", headers=headers, json=payload)
  print(response.text)
  if response.status_code == 200 and response.json()["status"] == "true":
    return response.json()["data"]["enableModels"]["state"]["status"]
  else:
    raise Exception("Custom exception")

if __name__ == "__main__": 
    get_intents()

Example Response

"data": {
    "sentiment": [
            {
                "startTime": 1390,
                "endTime": 2690,
                "speakers": [
                    "1"
                ],
    "similarityMatch": [
        {
          "matchedTextList": [
            {
              "score": 0.6180883955955505,
              "text": "Marsview is a great place to work",
              "value": "Marsview"
            }
          ],
          "intentId": "intent-bxllq2f7hpkrvtyzi3-1627981197627",
          "intentName": "Marsview"
        },
      ],    
    "phraseMatch": [
        {
          "matchedTextList": [
            {
              "score": 0.6180883955955505,
              "text": "Marsview is a great place to work",
              "value": "Marsview"
            }
          ],
          "intentId": "intent-bxllq2f7hpkrvtyzi3-1627981197627",
          "intentName": "Marsview"
        },
      ],             
      "sentence": "Marsview is a great place to work"
      },
    ]
}

Response Object

Field	Description
startTime	Start time of the sentence in the input Video/Audio in milliseconds.
endTime	End time of the sentence in the input Video/Audio in milliseconds.
speakers	A list of speaker id's whose voices are identified for a given time frame. Normally this list would only have a single speaker Id.
similarityMatch	The intent similarity output from the models
phraseMatch	The phrase match output from the models
intentId	The intent Id against which the sentences are matched
intentName	The name of the matching intent
score	The similarity matching score ranges from 0 to 1
text	The sentence which is used to predict intent for
value	The predicted intent
sentence	A sentence identified by the model in the given time frame.