Meetra AI
  • Welcome to Meetra AI API
  • Meetra AI Conversation Intelligence API Building Blocks
  • Meetra AI Conversation Intelligence API Reference
    • User Login
    • Upload Audio / Video material
    • Speaker Detection
    • Rename Speaker
    • Speaker Balance Score
    • Topic Dynamics & Details
    • Speaker Key Points
    • Conversation and Speaker Summaries
    • Conversation Topics and Keywords
    • Questions Asked
    • Conversation Transcript
    • Conversation Dynamics
    • Conversation Emotions
    • Speaker Emotions Over Time
    • Sentiment Score
    • Conversational Energy
    • Interaction Score
    • Interaction Strength Between Speakers
    • Speaker Audio Quality
    • Individual Speaker Balance
  • Built with Meetra AI
    • 🌟NorthStar
      • Example: Meeting Quality Analysis
  • Contact Us
  • Tech Stack and Models
    • Project Structure
    • Database Structure
    • General Audio Processing Flow
    • Security Considerations
    • Open Source Usage in the Codebase
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  • Group Dynamics Layer
  • Context Layer
  • Topic Deep Dive
  • Fluctuations

Meetra AI Conversation Intelligence API Building Blocks

Explore the key components of Meetra AI API

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Last updated 1 year ago

The Conversation Intelligence 2.0 Building Blocks are designed to provide a comprehensive understanding of group dynamics, context, topics, and fluctuations within a conversation. Here's a summary of each layer and its components:

Group Dynamics Layer

  • Speaker Detection: Identifies individual speakers in a conversation.

  • Conversational Energy: Measures the energy level in a conversation.

  • Conversational Sentiment: Analyzes the overall sentiment throughout a conversation.

  • Conversational Balance: Evaluates the balance of participation among speakers.

  • Interaction Mapping: Visualizes the strength of interactions between participants.

Context Layer

  • Conversation Transcripts: Provides full transcriptions of the conversation's audio content.

  • Conversation Summary: Offers a concise summary of the conversation.

  • Speaker Summaries: Generates summaries of each speaker's contributions.

  • Key Points and Questions: Identifies and lists key points and questions raised during the conversation.

  • Topics Discussed: Detects and lists topics discussed throughout the conversation.

Topic Deep Dive

  • Topic Indication: Lists topics discussed in the conversation

  • Topic Energy: Measures the energy associated with specific topics.

  • Topic Sentiment: Analyzes the sentiment around specific topics.

  • Topic Speakers: Identifies speakers who contributed to specific topics.

  • Topic Emotions: Uncovers the emotions related to particular topics.

Fluctuations

  • Energy Fluctuations: Tracks changes in energy levels throughout the conversation.

  • Sentiment Fluctuations: Monitors shifts in sentiment during the conversation.

  • Interaction Fluctuations: Observes variations in interaction strength between participants.

These building blocks work together to provide valuable insights into conversation dynamics, helping users better understand the nuances of group interactions, context, and emotions, as well as the evolution of energy and sentiment within the conversation.