Amazon Lex与Amazon Connect语音识别故障技术咨询

Hey there, let's break down the issues you're facing with your Lex bot integrated into Amazon Connect and walk through actionable fixes to get this sorted out:

This usually boils down to voice recognition or configuration mismatches between Connect and Lex. Try these checks:

• Verify Connect's voice input settings: In your contact flow, double-check that the automatic speech recognition (ASR) language matches your speaking language, and adjust the input timeout to a reasonable value (not too short). Mismatched languages or tight timeouts often trigger repeated prompts.
• Test Lex's voice recognition independently: Use Lex's built-in voice test (not just text) to confirm your voice commands are recognized correctly there. If Lex works fine alone, the issue is likely in Connect's audio pipeline or integration settings.
• Rule out audio quality issues: Background noise, low microphone volume, or poor softphone audio can wreck ASR accuracy. Test in a quiet space with a high-quality mic to eliminate environmental/hardware factors.
• Adjust Lex intent confidence thresholds: In the Lex console, each intent has a confidence threshold. If it's set too high (e.g., 0.9), Connect's ASR results might not meet the bar, causing repeat prompts. Try lowering it to 0.7 or 0.6 to see if recognition improves.

Let's tackle each slot separately:

Incident Description Slot #

• Confirm the slot type: If this is free-form text, make sure you're using AMAZON.SearchQuery or a custom free-text slot type—not an enumerated slot. Enumerated slots only match predefined values, so natural language descriptions will slip through.
• Check slot prompts & contact flow handoff: Ensure Lex has clear prompts for capturing the description (e.g., "Can you tell me more about the issue?") and that your contact flow isn't overriding or skipping this prompt. If the user isn't properly guided to input the description, Lex won't capture it.
• Inspect Lambda logs (if used): If you're using a Lambda function to handle slot data, check its logs to see if the description value is actually being passed from Lex. Sometimes the issue is in the Lambda code failing to extract the slot, not Lex failing to capture it.

Employee ID Slot #

• Use the right slot type: For employee IDs (especially if they're numeric or follow a fixed pattern), use AMAZON.Number for pure digits or a custom slot type with sample utterances that match how users would state their ID (e.g., "My employee ID is 12345", "Employee number is ABC789"). Adding enough sample phrases helps Lex's model recognize the pattern.
• Validate ASR output: Enable Lex conversation logs to see the exact text transcribed from your voice input. If the ASR is converting your employee ID to random numbers, you may need to add synonyms or expand sample utterances in Lex to teach the model to recognize your ID format.
• Check for format mismatches: If your employee IDs include letters or special characters, make sure your slot type isn't restricted to just numbers—custom slots let you define valid patterns with regular expressions, which can help filter incorrect recognitions.

• Test text input in Connect: Use the softphone's text input feature (if available) to type commands like "create an incident" and your slot values. If text works but voice doesn't, focus on fixing ASR/voice issues. If text also fails, revisit your Lex-Connect integration settings or Lex intent configuration.
• Review Connect's Lex integration step: In your contact flow, confirm that the "Invoke Lex" step is correctly configured to pass user input to your bot, and that it's set to continue capturing slots until all required ones are filled.

内容的提问来源于stack exchange，提问作者Arulvelu