Sentiment Analysis will help you interpret and quantify if the conversation in the audio or text is Positive, Negative, or Neutral. It also provides you a measure as to how subjective the conversation is with a subjectivity score.
See the table below for the output definition of the model
Sentiment | Description | Example |
Very Positive | a statement or sentence that is highly positive | "Brilliant work John, you really came through." |
Positive | a statement or a sentence that is marginally positive | "Okay let's hope everything is fine." |
Neutral | a statement or a sentence that is neutral | "..sure I will do that tomorrow" |
Very Negative | a statement or sentence that is highly negative | "I don't think that will happen today" |
Negative | a statement or a sentence that is marginally Negative | "I am not happy with the outcome.." |
Input Type Supported: Audio, Video
Model Dependency for Audio Input: Speech to Text, Speaker Separation
sentiment_analysis.enable key is set to true under the settings objectTransaction ID is returned in the JSON body once the processing job is launched successfully.
This Transaction ID can be used to check the status of the job or fetch the results of the job once the metadata is computed{"status":true,"transaction_id":32dcef1a-5724-4df8-a4a5-fb43c047716b,"message": " Compute job for file-id: 32dcef1a-5724-4df8-a4a5-fb43c047716b launched successfully"}
Speech to Text has to be enabled for Action Items to be enabled){"status":false,"error":{"code":"MCST07","message":"DependencyError: emotion_analysis depends on speech_to_text"}}
curl --request POST 'https://api.marsview.ai/v1/conversation/compute' \--header 'appSecret: 32dcef1a-5724-4df8-a4a5-fb43c047716b' \--header 'appId: 1ZrKT0tTv7rVWX-qNAKLc' \--header 'Content-Type: application/json' \--data-raw '{"settings":{"speech_to_text":{"enable":true,"pii_detection":false,"custom_vocabulary":["Marsview" , "Pikachu"]},"speaker_separation":{"enable":true,"num_speakers":4},"sentiment_analysis":{"enable":true,"sync_with_stt":true}}}'
Given below is a sample response JSON when the Status code is 200.
{"status":true,"transaction_id":32dcef1a-5724-4df8-a4a5-fb43c047716b,"message": " Compute job for file-id: 32dcef1a-5724-4df8-a4a5-fb43c047716b launched successfully"}
data object returns the requested metadata if it is computed. The status object shows the current state of the requested metadata. Status for each metadata field can take values "Queued"/"Processing"/"Completed".
Shown below is a case where "sentiment analysis" Job is in "Queued" state and "Completed" state. {"status":{"sentiment_analysis":"Queued",}"data":{"sentiment_analysis":{}}}
{"status":{"sentiment_analysis":"Completed"}"data":{"sentiment_analysis":{"chunks":[...{"start_time" : "174100.0""end_time" : "175100.0","sentiments" : [{"sentiment":"Very Positive","confidence":0.81},{"sentiment":"Positive","confidence":0.17},]},{"start_time" : "174100.0""end_time" : "175100.0","sentiments" : [{"sentiment":"Neutral","confidence":0.97}]},...]}}}
Fields | Description |
| Starting time of the chunk in milliseconds |
| Ending time of the chunk in milliseconds |
| List of sentiment objects for that particular chunk |
| Name Tag for the Type of sentiment detected. |
| Confidence of the sentiment (ranges from 0 to 1). Higher the better |