Speech SDK – Inconsistent Speech-to-Text Recognition Accuracy

Anandu K B 0 Reputation points
2025-08-26T12:53:11.0533333+00:00

We are currently facing issues with Azure Speech Service using the Speech SDK for voice-to-text recognition. The service is not providing consistent and accurate transcriptions.

Issues observed:

Some words are being completely missed during recognition.

In some cases, incorrect words are being recognized instead of the spoken ones.

The issue occurs intermittently across different sessions.

Impact: This inconsistency is affecting the user experience of our application where accurate transcription is critical.

Request: Please investigate if this issue is related to the Speech SDK, underlying service models, or any configuration limits. Kindly provide guidance or possible resolutions to improve recognition accuracy.

Azure AI Speech
Azure AI Speech
An Azure service that integrates speech processing into apps and services.
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  1. Sina Salam 24,096 Reputation points Volunteer Moderator
    2025-08-26T15:39:21.7033333+00:00

    Hello Anandu K B,

    Welcome to the Microsoft Q&A and thank you for posting your questions here.

    I understand that you are having inconsistent Speech-to-Text Recognition Accuracy in Speech SDK for your AI Speech.

    Since the problem is intermittent, it confirms that while the service itself is functional, your specific usage pattern or input data is causing the unpredictability.

    Therefore, you must first eliminate client-side variables by testing with identical audio files to isolate service-side issues. Then, enforce consistency by ensuring your audio input always meets optimal format requirements and implement detailed logging to capture confidence scores for each recognition result. The most critical step is to quantify the error rate objectively using Speech Studio's accuracy testing.

    For better resolution:

    1. Validate audio format compliance: https://learn.microsoft.com/en-us/azure/ai-services/speech-service/how-to-use-audio-input-streams
    2. Implement detailed logging with word-level timestamps:
    config.SetServiceProperty("wordLevelTimestamps", "true", ServicePropertyChannel.UriQueryParameter);
        config.OutputFormat = OutputFormat.Detailed;
    
    1. Quantify errors with Speech Studio testing: https://learn.microsoft.com/en-us/azure/ai-services/speech-service/how-to-custom-speech-evaluate-data
    2. For persistent issues, contact support with specific audio samples and timestamps from failed sessions correlated with Azure status history - https://status.azure.com/status via your Azure Portal.

    I hope this is helpful! Do not hesitate to let me know if you have any other questions or clarifications.


    Please don't forget to close up the thread here by upvoting and accept it as an answer if it is helpful.

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