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copied!<p>I am not sure exactly which wave file you are talking about (I haven't spoken French since middle school). But I think this wave from your group qualifies: dump_2012_12.16_12.47.33.wav. It has a high confidence value .857 and does not appear to have any speech in the audio file. Looking at a spectrogram (see below) you can see the audio file does contain energy in the speech range. <img src="https://i.stack.imgur.com/i6nJV.png" alt="enter image description here"></p> <p>Most speech recognition engines these days use a Hidden Markov Model (aka HMM) to match audio vector patterns to speech. The state of the art today is not always accurate at doing this. HMM's tend to be really sensitive to background noise. </p> <p>This is why most speech type features in production today (like Siri) are push to talk. You need to push a button and you have 5 seconds to speak into the microphone. They do this so they can be sure there is some type of speech signal. For those systems that are open mic (Kinect is the only one I know of) they try and use a form of echo cancellation to suppress background audio. But even with the state of the art there is still bleed through. </p> <p>The only relatively easy work arounds (again not 100%) that I know of involve editing your grammar to include a garbage rule and shortening the possible phrase list. The garbage rule will give the speech engine a "run home to momma" option when it does not know what to do.</p> <p><a href="http://www.w3.org/TR/speech-grammar/#S2.2.3" rel="nofollow noreferrer">http://www.w3.org/TR/speech-grammar/#S2.2.3</a> </p> <p>Although I don't think this is recommended usage I have seen some systems behave better when using the garbage rule to help filter out background noise. Of course they then have to ignore the garbage reco events.</p>

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