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There are two "inputs" into Wavenet: the previously generated samples of the waveform, which are usually encoded into multiple channels, like into 256 channels using 8-bit mu-law encoding local conditioning, which can be things like linguistic features such as phoneme classes (used in the original wavenet paper), or frequencies like mel ...


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The problem you state is a well known problem, and it is called "keyword spotting" os KWS. If you add a wake up word before it (like "hey google/siri"), you can also use "voice command" system to alleviate the problem. There are two kind of KWS systems: those which develop to detect a hard coded set of keywords, and those who ...


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