Comments (2)
It depends what you mean. If you have labeled recordings of a speaker and want to recognize those exact recordings being played, then yes.
If however you want to recognize (1:N) or verify (1:1) a person's speech by their particular idiosyncrasies of speech, then no. dejavu
works off of a fingerprinting (read: hashing) system. Like any good hashing scheme, a small perturbation of the input (in dejavu
's case, timing and frequency) will cause very different fingerprints.
While very robust to noise, trying to recognize voice, which is not reliably the same timing or frequency each time, won't work. dejavu
is meant for recognizing exact duplicates of previously recorded audio.
from dejavu.
I was thinking about having a long recording of an individual repeating their name many times, and then as input having them say their name once. The fingerprinting approach may be useful there. I or a friend will try it out when we get a chance and get back to you.
Thanks!
from dejavu.
Related Issues (20)
- Alot of decrepated attributes.... HOT 5
- Song Returns 'none'
- does it suport no database? HOT 3
- out of memory when use mysql HOT 3
- AttributeError: 'numpy.int64' object has no attribute 'read'
- Possibility of partial match HOT 5
- confusion between mp3 folder and test folder
- Which field in the results indicates the best match with the original song HOT 3
- run_tests.py: error: the following arguments are required src HOT 4
- Trying to fingerprint about 200 000 files. After 15000 files INSERT operation is very slow. HOT 1
- Do maximum_filter with cupy instead of scipy
- Failed to solve HOT 1
- Comparing short audio files
- Python Docker image bloated
- A directory of potentially duplicate audio files?
- it works well with python3.6 ~
- Not working for recordings
- Some errors when I use python3.7
- multiple concurrency
- Fingerprinting Audio With Differing Sample Rates HOT 1
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from dejavu.