Chinese version recognition issues

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    Hi Hello,

    Thank you for your previous answers that give us a lot important informations which are really help in solving our issues.

    Now, we have some problems in Chinese recognition.

    In my own test-use phone, Chinese recognition works well, but when we test more Iphones, we didn’t get expected recognition rate( especially for iphone 7).

    Like in my test phone, Openears recognize fast and accurate, in other test phones, situations are different. sometimes it recognize the word accurate but with a long delay(like 2 or 3 seconds), sometimes it works well at first, but get low recognition rate later, sometimes it just didn’t react to voice command.

    Since it works well in my own phone( also English version works well with same logic), i dont think it is the logic problem of my code.

    So do you have any idea for this? or any hint and directions i may need to do the research on to solve this issue?

    Thank you,

    Halle Winkler

    Hi Xi,

    Sorry, no specific ideas, but you can collect audio of these cases for your own QA so you can investigate issues with your app when people outside of your team are using it. OpenEars has two features that can help you undertake your QA: the first is that you can collect audio of other users’ OpenEars sessions using SaveThatWave (you can use the demo version for the purpose of collecting problem audio without buying the plugin as long as you don’t ship your SaveThatWave-enabled version to the App Store) using its method startSessionDebugRecord to obtain all speech for an entire app session as a WAV, and then once you have this WAV and add it to your bundle, you can use OpenEars’ method pathToTestFile in order to replay the session in your app, which may show you what is happening when there is a problem. Then you can (for instance) try different words in your model or change the vadThreshold or the other standard troubleshooting steps available to you. You will also need to collect info about which devices and OS versions are being used in case you need to break out separate logic for those cases.

    Sorry, it isn’t possible for me to troubleshoot very generalized issues such as a model which works well for some speakers and less well for others (this is a standard issue in speech recognition), but if you do your own QA and see something that could be reported as a specifiable and replicable bug, please feel free to let me know about it.

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