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Autotuning Google Text-to-Speech
Hi,
I come from a research team which works on bugs in real-world applications.
I want to make a report about a few potential performance improvement in your project.
In file generate.py
, it downloads word-wise audio using Google synthesize_speech
API sequentially. However, as cloud APIs do not compete resources locally, calling them in parallel would greatly reduces the execution time.
Google synthesize_speech
API actually also returns time info of the transcript. It would be more time efficient to feed several words to the API and chunk later. As there's a cold start time, two 1-word audios usually takes much longer time than one 2-word audio.
Perhaps someone might be able to confirm if these seem reasonable. Also, if you need any help, I'm happy to provide some code snippet for fixing.
If you are not offended by it, we may include your response as a percentage number (e.g. xx% of applications faces xx problem, and xx% of them confirms it) in our research paper.
Thanks.
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