3 ms·

There are so many comments about the "real" length of the program. The number 284 means something to people who work in speech recognition - these are the peop

There are so many comments about the "real" length of the program. The number 284 means something to people who work in speech recognition - these are the people that know how much _they_ write when they try to compete with this library. This number isn't meant for people who are disinterested (have no stake) in speech recognition.

deleted 4y ago
[deleted]
prewett 4y ago
"X in N lines of code" is usually used for compressing an algorithm down to its bare essentials. "Ray tracing in 100 lines of code". In that case, it's disingenuous to have 100 lines of glue code that calls into pov-ray. If I compile 284 lines of code, I expect a few kb executable (including libraries that aren't language-libraries like libc). This hasn't really simplified the speech-recognition algorithm, it still requires large amounts of training data and time, and still does the speech recognition by solving a large matrix with Tensorflow. It's not interesting to me that you can hook up Tensorflow in a few lines of code; I know Tensorflow can solve the problem. However, I would be interested in 284 lines of code that replace Tensorflow, which is what the title suggested to me. A better title would be to focus on how the model and/or the handling of the data produces better results, because that's what this code seems to be about.
- fxtentacle 4y ago
  If you compare this with Mozilla's DeepSpeech repository, you will find that correctly calling TensorFlow Lite and handling the results in only 284 lines of code is impressive, too. Also, the C++ code is mostly a custom beam search decoder based on the research for my paper, so it's not like TensorFlow is doing all the heavy lifting here, because precisely that TEVR token decoder causes the relative 16% performance improvement of this speech recognition AI over others.

3 ms·

There are so many comments about the "real" length of the program. The number 284 means something to people who work in speech recognition - these are the peop

by henrydark 4y ago

deleted 4y ago
[deleted]
prewett 4y ago
"X in N lines of code" is usually used for compressing an algorithm down to its bare essentials. "Ray tracing in 100 lines of code". In that case, it's disingenuous to have 100 lines of glue code that calls into pov-ray. If I compile 284 lines of code, I expect a few kb executable (including libraries that aren't language-libraries like libc). This hasn't really simplified the speech-recognition algorithm, it still requires large amounts of training data and time, and still does the speech recognition by solving a large matrix with Tensorflow. It's not interesting to me that you can hook up Tensorflow in a few lines of code; I know Tensorflow can solve the problem. However, I would be interested in 284 lines of code that replace Tensorflow, which is what the title suggested to me. A better title would be to focus on how the model and/or the handling of the data produces better results, because that's what this code seems to be about.
- fxtentacle 4y ago
  If you compare this with Mozilla's DeepSpeech repository, you will find that correctly calling TensorFlow Lite and handling the results in only 284 lines of code is impressive, too. Also, the C++ code is mostly a custom beam search decoder based on the research for my paper, so it's not like TensorFlow is doing all the heavy lifting here, because precisely that TEVR token decoder causes the relative 16% performance improvement of this speech recognition AI over others.