fgnt / pb_bss Goto Github PK
View Code? Open in Web Editor NEWCollection of EM algorithms for blind source separation of audio signals
License: MIT License
Collection of EM algorithms for blind source separation of audio signals
License: MIT License
hi dear author:
Could you give an instruction to show how to run your project please?
Thanks.
Hello,
When i run activity_alignment.py(Generate finetuned time annotations from kaldi worn alignments), there is something wrong ,The following information is an error message:
ERROR - Chime5 Array Enhancement - Failed after 1 day, 10:27:41!
Traceback (most recent calls WITHOUT Sacred internals):
File "/kaldi/egs/chime6/pb_chime5/pb_chime5/scripts/run.py", line 91, in main
run(_run)
File "/kaldi/egs/chime6/pb_chime5/pb_chime5/scripts/run.py", line 128, in run
audio_dir_exist_ok=True
File "/kaldi/egs/chime6/pb_chime5/pb_chime5/core_chime6.py", line 381, in enhance_session
x_hat = self.enhance_example(ex)
File "/kaldi/egs/chime6/pb_chime5/pb_chime5/core_chime6.py", line 495, in enhance_example
debug=debug,
File "/kaldi/egs/chime6/pb_chime5/pb_chime5/core_chime6.py", line 533, in enhance_observation
masks = self.gss_block(Obs, acitivity_freq, debug=debug)
File "/kaldi/egs/chime6/pb_chime5/pb_chime5/core_chime6.py", line 183, in call
source_activity_mask=source_active_mask[f, ..., :T],
File "/kaldi/egs/chime6/pb_chime5/pb_chime5/pb_bss/pb_bss/distribution/cacgmm.py", line 223, in fit
initialization.shape, affiliation_shape
AssertionError: ((5, 1140), (5, 1165))
Do you know what I should do to solve this problem
Hi,
Both InputMetrics
and OutputMetrics
have the as_dict
function which returns all the metrics as a dict. I think this is a nice UI but it would be even nicer to be able to control which metric is going to be computed without calling them one by one, what do you think?
Something like this might do, with more
Index: pb_bss/evaluation/wrapper.py
===================================================================
--- pb_bss/evaluation/wrapper.py (revision 8c31ef0b1e32d355f468170f07e41f989d8cf4c6)
+++ pb_bss/evaluation/wrapper.py (date 1579701195206)
@@ -318,6 +318,18 @@
return_dict=True,
)
+ def sdr(self):
+ return self.mir_eval['sdr']
+
+ def sir(self):
+ return self.mir_eval['sir']
+
+ def sar(self):
+ return self.mir_eval['sar']
+
+ def selection(self):
+ return self.mir_eval['selection']
+
@cached_property.cached_property
def pesq(self):
return pb_bss.evaluation.pesq(
@@ -342,6 +354,15 @@
)
return invasive_sxr
+ def invasive_sdr(self):
+ return self.invasive_sxr['sdr']
+
+ def invasive_sir(self):
+ return self.invasive_sxr['sir']
+
+ def invasive_sar(self):
+ return self.invasive_sxr['sar']
+
@cached_property.cached_property
def stoi(self):
return pb_bss.evaluation.stoi(
@@ -383,3 +404,8 @@
metrics['invasive_sxr_snr'] = self.invasive_sxr['snr']
return metrics
+
+ def get_as_dict(self, *metric_names):
+ metrics = dict()
+ for m in metric_names:
+ metrics[m] = self.__getattribute__(m)
I'm willing to put more efforts into it if you'd be interested of course.
Is there any plan to support install pb_bss from pypi?
Hi, I'm a little confused about the SDR in the output metrics. In the paper https://arxiv.org/pdf/1811.02508.pdf, it referred to the original SNR. Does the SDR also refer to SNR in this toolkit? Or it refers to the SD-SDR.
Hi,
What's the motivation behind those lines?
Why not float32 for scale invariant SDR?
dear friend:
Could you give one instruction to show how to run the example please?
Thanks.
Would you consider making pb_bss.evaluation
a standalone python package?
I'm annoying, I know but this is not really user friendly ;-)
Is paderbox open-source? I cannot find it
On a fresh python install
git clone https://github.com/fgnt/pb_bss
cd pb_bss
pip install numpy Cython
pip install -e .
pip install -e .
pip install -e .
Ends up working
After some discussions in #25, it turned out, that it would be good to update the example.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.