Introduction
These are the slightly modified tensorflow/python implementation of recent speaker recognition papers. Please tell me if it is copyright infringement, I'll delete these paper as soon as I can. Our license only apply to our code these paper is not included. Thx.
The file structure is as follows：
|———pyasv
|
|—————model (folder, contain the model)
|
|—————loss (folder, contain the customized loss function)
|
|—————papers (folder, contain the origin paper of most of method)
|
|—————backend(TODO: folder, contain the method of backend)
|
|———data_manage.py (contain some method to manage data)
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|———speech_processing.py (contain some method to extractfeature and process audio)
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|———config.py (settings. e.g. save path, learning rate)
More info: Doc
If you want run these code on your computer, you only need to write code like this:
from pyasv import Config
from pyasv.speech_processing import ext_mfcc_feature
from pyasv.data_manage import DataManage
from pyasv.model.ctdnn import run
config = pyasv.Config(name='my_ctdnn_model',
n_speaker=1e3,
batch_size=64,
n_gpu=2,
max_step=100,
is_big_dataset=False,
url_of_bigdataset_temp_file=None,
learning_rate=1e-3,
slide_windows=[4, 4]
save_path='/home/my_path')
config.save('./my_config_path')
frames, labels = ext_mfcc_feature('data_set_path', config)
train = DataManage(frames, labels, config)
frames, labels = ext_mfcc_feature('data_set_path', config)
validation = DataManage(frames, labels, config)
run(config, train, validation)TODO
- Implement papers of ICASSP 2018 & Interspeech 2018.
- Compare each model on a same dataset.
Implemented papers:
- L. Li, Z. Tang, D. Wang, T. Zheng, "Deep Speaker Feature Learning for Text-Independent Speaker Verification."
- L. Li, Z. Tang, D. Wang, T. Zheng, "Full-info Training for Deep Speaker Feature Learning," ICASSP 2018.
- C. Li, X. Ma, B. Jiang, X. Li, X. Zhang, X. Liu, Y. Cao, A. Kannan, Z. Zhu, "Deep Speaker: an End-to-End Neural Speaker Embedding System."
- Sergey Novoselov, Oleg Kudashev, Vadim Shchemelinin, Ivan Kremnev, Galina Lavrentyeva, "DEEP CNN BASED FEATURE EXTRACTOR FOR TEXT-PROMPTED SPEAKERRECOGNITION."