Chatbot Overview
Conversational Bots
Intents & Entities
Intelligent Bots's Approach Conversational Platform
Bot Concepts and Terminology
Natural Language Processing (NLP)
Bot Types
Bot Tasks
Starting with Platform
How to Access Bot Builder
Working with Bot Builder
Building your first Bot
Getting Started with Building Bots
Using the Dialog Builder Tool
Creating a Simple Bot
Release Notes
Latest Updates
Older Releases
Bot Builder
Creating a Bot
Dialog Task
User Intent Node
Dialog Node
Entity Node
Supported Entity Types
Composite Entities
Supported Time Zones
Supported Colors
Supported Company Names
Form Node
Logic Node
Message Nodes
Confirmation Nodes
Service Node
Custom Authentication
2-way SSL for Service nodes
Script Node
Agent Transfer Node
WebHook Node
Grouping Nodes
Connections & Transitions
Managing Dialogs
User Prompts
Alert Tasks
Alert Tasks
Ignore Words and Field Memory
Digital Forms
Digital Views
Knowledge Graph
Importing and Exporting
Knowledge Extraction
Small Talk
Action & Information Task
Action Tasks
Information Tasks
Establishing Flows
Natural Language
Machine Learning
ML Model
Fundamental Meaning
NLP Settings and Guidelines
Knowledge Graph Training
Ranking and Resolver
NLP Detection
Advanced NLP Configurations
Bot Intelligence
Context Management
Session and Context Variables
Context Object
Dialog Management
Amend Entity
Multi-Intent Detection
Sentiment Management
Tone Analysis
Sentiment Management
Default Conversations
Default Standard Responses
Channel Enablement
Test & Debug
Talk to Bot
Utterance Testing
Batch Testing
Record Conversations
Publishing your Bot
Analyzing your Bot
Custom Dashboard
Conversation Flows
Bot Metrics
Advanced Topics
Bot Authorization
Language Management
Collaborative Development
IVR Integration
Data Table
Universal Bots
Enabling Languages
Smart Bots
Sample Bots
Travel Planning
Flight Search
Event Based Bot Actions
koreUtil Libraries
Bot Settings
Bot Functions
General Settings
PII Settings
Customizing Error Messages
Manage Sessions
Bot Management
Bot Versioning
Using Bot Variables
API Guide
API Overview
API List
API Collection
SDK Overview
SDK Security
SDK App Registration
Web SDK Tutorial
Message Formatting and Templates
Mobile SDK Push Notification
Widget SDK Tutorial
Widget SDK – Message Formatting and Templates
Web Socket Connect & RTM
Using the BotKit SDK
BotKit SDK Tutorial – Agent Transfer
BotKit SDK Tutorial – Flight Search Sample Bot
Using an External NLP Engine
Bot Administration
Bots Admin Console
User Management
Managing Users
Managing Groups
Managing Role
Bots Management
Inviting Users
Bulk Invites
Importing Users
Synchronizing Users from AD
Security & Compliance
Using Single Sign-On
Security Settings
Cloud Connector
How Tos
Creating a Simple Bot
Creating a Banking Bot
Transfer Funds Task
Update Balance Task
Context Switching
Using Traits
Schedule a Smart Alert
Configure Digital Forms
Add Form Data into Data Tables
Configuring Digital Views
Add Data to Data Tables
Update Data in Data Tables
Custom Dashboard
Custom Tags to filter Bot Metrics
Patterns for Intents & Entities
Build Knowledge Graph
Global Variables
Content Variables
Using Bot Functions
Configure Agent Transfer
  1. Home
  2. Docs
  3. Bots
  4. Advanced Topics
  5. Tone Analysis

Tone Analysis

The Bots Platform Natural Language Processing (NLP) interpreter can parse user utterances for specific words and phrases, and then provide an average tone score based on the connotation, word placement, and any added modifiers. You can use the score to help assess the user input and direct the flow of the conversation between the Bot and the user.

For example, if the tone score indicates a user is angry or sad, you might want to transition the bot conversation to a live agent. In a dialog task, you can access the tone score from the Context object. Or you can configure events to be triggered, from the Sentiment Management option under Intelligence.

Tones Types Bots Platform evaluates user inputs to find the following six possible emotions:

  • angry
  • disgust
  • fear
  • sad
  • joy
  • positive – A special tone used to evaluate the general positivity of an utterance.

The Bots Platform tone algorithm provides a nuanced overview of the user utterance tone by not making the emotions mutually exclusive. For example, an input could yield a high score for fear and a mild score for sadness. Another input could yield a very high score for joy while having a negative score for sadness.

Scoring Tone Emotions

The Bots Platform scores a tone emotion on a scale range of -3 to +3 where positive values represent an expressed tone emotion and a negative value represents a suppressed tone emotion.

For positive values, the tone emotion is explicitly communicated, while negative values are explicitly negated.

For example, a user utterance, “I am happy about this news” returns a positive tone score for joy, while “I am not happy about this news” returns a negative score for joy.

The following scale shows the relationship of the score to the level of positive expression of the tone emotion or negative suppression of the tone emotion.

  • +3 – The user definitely expressed the tone emotion.
  • +2 – The user expressed the tone emotion.
  • +1 – The user likely expressed the tone emotion.
  • 0 – The user tone emotion is neutral.
  • -1 – The user likely suppressed the tone emotion.
  • -2 – The user suppressed the tone emotion.
  • -3 – The user definitely suppressed the tone emotion.

About Tone Scores

The overall tone score is calculated as a function of the base tone value and any tone modifiers. Modifiers are generally adverbs or adjectives that supplement a tone emotion word, either to increase or decrease the base tone score.

For example, a user utterance as “I am extremely disappointed” returns a higher tone score for the angry tone emotion than if the user utterance is “I am disappointed.” Conversely, a user utterance of “I am not disappointed” negates the tone emotion and the tone score.

The value of the base tone and modifiers are used to calculate the final tone score for each tone emotion. The tone analyzer compiles all base tones based on the tone emotion type and then calculates the average score of each tone emotion type in the current dialog task node and the tone total score since the last reset.

Tone results are returned as Context object variables as:

  • message_tone – An array of recognized tone emotions and scores for the current node in a dialog task.
  • dialog_tone – An array of average recognized tone emotions and scores for the entire dialog task session. This value is reset at the end of each dialog session.

Each variable is populated with key/value pairs for each recognized tone emotion. Key/value pairs are not returned if a tone is not detected for an emotion. However, the NLP engine returns a tone score of 0 when a tone is recognized as neutral. When you access tone variables in the Context object, you must be able to handle positive, negative, zero, as well as undefined results.


      tone_name : positive
      level : 2
      tone_name : disgust
      level : -2
      tone_name : angry
      level : -2
      tone_name : angry
      level : -3
      tone_name : sad
      level : -3
      tone_name : positive
      level : 3
      tone_name : joy
      level : 3

Here are some examples of test sentences with their associated tone emotion scores:
“I don’t think that this is a good idea and I am not happy with how it came out, especially because of your attitude.”

      tone_name : joy
      count : 1
      level : 0.67
      tone_name : sad
      count : 1
      level : 0.5
      tone_name : angry
      count : 1
      level : 0.5

“This is a great idea! I’m super excited already.”

      tone_name : joy
      count : 1
      level : 3
      tone_name : sad
      count : 1
      level : 2.8
      tone_name : angry
      count : 1
      level : -3

“This was a funny and casually well-written book, a good read. But it’s a little frustrating because it abandons the “narrative”, if you will, without finishing it.”

      tone_name : joy
      count : 1
      level : 1.5
      tone_name : sad
      count : 1
      level : -1.5
      tone_name : angry
      count : 1
      level : -1

You can access and use tone scores to help drive the flow of your dialog task using conditional transition statements, for example,

if context.message_tone.angry > 2.0
    then goTo liveAgent

For more information, see Context Object.