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CustomEndpointingRules for StartSpeakingPlan not w...
# support
a
I created a rule which matches "hello" so latency speeds up at the beginning of the call. I've tried "hello" and "hello.*". Shared a screenshot. Why is the endpointing > 0, if my endpointing rule matches? This is what my assistant override looks like
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"startSpeakingPlan": {
      "customEndpointingRules": [
        {
          "type": "customer",
          "regex": "hello",
          "timeoutSeconds": 0,
          "regexOptions": [
            {
              "enabled": true,
              "type": "ignore-case"
            },
            {
              "enabled": true,
              "type": "multi-line"
            }
          ]
        }
      ]
    }
https://cdn.discordapp.com/attachments/1346641632413356043/1346641632887308409/Screenshot_2025-03-04_at_7.29.01_PM.png?ex=67c8ed40&is=67c79bc0&hm=f07d8636b0f52ab52e92fb61066f1310a78b082157a13bacd031764cc92c6ea8&
v
It looks like you're experiencing an issue where the endpointing is greater than 0, even though your custom endpointing rule for "hello" should match. Here are a few potential reasons for this behavior: 1. **Heuristic Rule Conflict**: The logs indicate that the endpointing timeout is being triggered by a heuristic rule, which may have a default timeout (in this case, 600ms). This can override or conflict with your custom rule, especially if the heuristic rule is set to take precedence. 2. **Configuration Settings**: Ensure that your custom endpointing rule is correctly configured. The 
timeoutSeconds
is set to 0, which means it should respond immediately when "hello" is detected. However, if the heuristic rule is still active, it may still impose its own timeout. 3. **Regex Matching**: While your regex for "hello" should match, consider testing with variations like "hello.*" to ensure it captures all intended inputs. However, since you mentioned you've already tried that, the issue might lie elsewhere. 4. **Background Noise and Voice Filtering**: If there is background noise or if the audio input isn't clear, it might affect the detection of your custom rule. Make sure the audio quality is good and that noise filtering is in place. 5. **Testing and Logging**: It might be helpful to log additional details or test with different phrases to see how the system responds. This can help identify if the issue is specific to the "hello" input or if it occurs with other phrases as well. To resolve this, you might want to adjust the priority of your custom rules or review the settings for the heuristic rules to ensure they don't conflict. If the problem persists, further testing and adjustments may be necessary. Let me know if you need more help! 😊 Sources: - [Vapi Documentation How Vapi Works](https://docs.vapi.ai/how-vapi-works) - [Vapi Documentation Glossary](https://docs.vapi.ai/glossary)
It looks like you're experiencing an issue with endpointing values being greater than 0, even though your custom endpointing rule matches "hello" with a timeout of 0 seconds. Here are a few potential reasons for this behavior: 1. **Heuristic Endpointing Rule**: The log indicates that the endpointing timeout is being triggered by a heuristic rule, which may take precedence over your custom rule. This can lead to a default timeout being applied, resulting in endpointing values greater than 0. 2. **Audio-Text Fusion Model**: Vapi uses a fusion model that considers both audio and text inputs. If the model detects pauses or other speech patterns that suggest the user hasn't finished speaking, it may extend the endpointing duration despite your custom rule. 3. **Background Noise or Speech Recognition Delays**: If there is background noise or if the speech recognition is delayed, it can affect how quickly the system recognizes the end of speech, leading to higher endpointing values. 4. **Configuration of Other Timeout Settings**: Ensure that other timeout settings, such as 
silenceTimeoutSeconds
, are configured correctly. If these settings conflict with your custom rule, they can cause unexpected behavior. To troubleshoot further, you might want to check the following: - Review the configuration of your heuristic rules and see if they are conflicting with your custom rule. - Test the system in a quieter environment to see if background noise is affecting the recognition. - Consider adjusting the timeout settings to see if that impacts the endpointing behavior. If you have any more questions or need further assistance, feel free to ask! 😊 Sources: - [Understanding Endpointing in Vapi](https://docs.vapi.ai/how-vapi-works) - [Detailed Report on Timeout Setting in Custom Endpointing Rules Affecting Vapi Behavior](https://discord.com/channels/1211482211119796234/1211483291191083018/1344633027925377064)
- [Best Practices for Configuring Custom Endpointing Rules in Vapi to Ensure Low Latency](https://discord.com/channels/1211482211119796234/1211483291191083018/1337135526981140621)
a
@Shubham Bajaj @Sahil Is that the issue? Conflict of prioritization? how do I tell the model to prioritize my CustomEndpointing to check for "hello"?
s
You've created a custom endpointing rule to match "hello" in customer speech with 0 seconds timeout, but you're still seeing endpointing latency in your calls. The issue likely stems from how the endpointing rules interact with the transcription endpointing plan. TLDR: While your rule matches and returns a 0ms delay, there might be other factors affecting the final endpointing timing.
To help track down this issue, could you share: - The call ID This would really help us figure out what went wrong!
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