---
title: "Conversationa Analytics"
slug: "dataflow-nodes-conversational-analytics-conversation-analyzer"
updated: 2025-05-27T14:11:15Z
published: 2025-05-27T14:11:15Z
canonical: "docs.knovvu.com/dataflow-nodes-conversational-analytics-conversation-analyzer"
---

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.knovvu.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Conversation Analyzer

Analyzes conversation speech. This node detects:
- The level of tension between the parties involved
- Interruptions in each other's speech
- Speaking rates (number of words per second)
- Periods of silence when both parties remain quiet
- Hesitations
- Sentiment of the speech text
- Speech overlaps

## Inputs

### Events
| name | description |
|---|---|
| [SR Milestone](/v1/docs/events#sr-milestone)| Most of the fields examined by the Conversation Analyzer are provided by this event. Features such as silence durations, speech rates, interrupts, and other characteristics are obtained by compiling channel-based events from the sr-milestone |
| [Emotion](/v1/docs/events#emotion)| The information from the emotion service is compiled to be displayed in the output based on segment and channel. For example, it can be provided that the agent channel exhibits "angry" sentiment between 4-8 seconds. |
| [Sentiment](/v1/docs/events#sentiment) |The results from the sentiment service are analyzed on an agent-customer basis, and the sentiment information of each segment is reflected in the outcome. |

### Audio
 none

## Outputs
### Event
| name  | description
|---|---| 
|[Conversation Analyzer Result](/v1/docs/events#conversation-analyzer-result)|A complete acoustic and text based analysis of the conversation. |

### Audio
 none

## Remarks 
To obtain data from the Conversation Analyzer, it is necessary to configure it along with the events listed in the "Input" field.

### Project Structure

Conversation Analyzer is one of the most complex nodes that requires the output from several nodes working together. The project structure can be seen in the *default project* `ca-offline`. The node requires the `agent` and `customer` to be separated into two channels. If a mono audio input is given, [Speaker Diarizer Node](/v1/docs/dataflow-nodes-speaker-diarizer)is utilized to do the separation. Then, the appropriate audio segments are filtered and used for [Gender](/v1/docs/dataflow-nodes-gender), [Emotion](/v1/docs/dataflow-nodes-emotion), [Sentiment](/v1/docs/dataflow-nodes-sentiment) analysis.  

[Audio Segment Picker](/v1/docs/dataflow-nodes-audio-segment-picker) and [Flush Barrier](/v1/docs/flush-barrier) are utilized, so that the most appropriate segment (5000-10000 milliseconds) is picked for [Language Identification](/v1/docs/dataflow-nodes-language-identifier) before the transcripts are generated in the [SR Http](/v1/docs/dataflow-nodes-speech-recognition-sr-http) node.
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### Supported flow types
Batch

## Release Notes

<div style="max-height: 200px; overflow-y: auto; overflow-x: hidden">
    <details>
        <summary> <strong> v1.0.0 </strong> </summary>
        <ul>
            <li> Introduced Node.</li>
        </ul>
    </details>
</div>