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Meetra AI Conversation Intelligence API Building Blocks
Explore the key components of Meetra AI API
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:
- 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.
- 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 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.
- 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.