提交 8d9bd9a9 编写于 作者: Q qingen

[vec][score] update Copyright, test=doc fix #1667

上级 44c66234
# Copyright (c) 2022 SpeechBrain Authors. All Rights Reserved. # Copyright (c) 2022 PaddlePaddle and SpeechBrain Authors. All Rights Reserved.
# #
# Licensed under the Apache License, Version 2.0 (the "License"); # Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License. # you may not use this file except in compliance with the License.
......
# Copyright (c) 2022 SpeechBrain Authors. All Rights Reserved. # Copyright (c) 2022 PaddlePaddle and SpeechBrain Authors. All Rights Reserved.
# #
# Licensed under the Apache License, Version 2.0 (the "License"); # Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License. # you may not use this file except in compliance with the License.
...@@ -569,7 +569,7 @@ if __name__ == '__main__': ...@@ -569,7 +569,7 @@ if __name__ == '__main__':
te_sgs = ['te' + str(i) for i in range(te_N)] te_sgs = ['te' + str(i) for i in range(te_N)]
te_sets = numpy.array(te_sgs, dtype="|O") te_sets = numpy.array(te_sgs, dtype="|O")
te_stat = EmbeddingMeta(modelset=te_sets, segset=te_sets, stats=te_xv) te_stat = EmbeddingMeta(modelset=te_sets, segset=te_sets, stats=te_xv)
ndx = Ndx(models=en_sets, testsegs=te_sets) ndx = Ndx(models=en_sets, testsegs=te_sets) # trials
# PLDA Scoring # PLDA Scoring
scores_plda = plda.scoring(en_stat, te_stat, ndx) scores_plda = plda.scoring(en_stat, te_stat, ndx)
print(scores_plda.scoremat.shape) #(20, 30) print(scores_plda.scoremat.shape) #(20, 30)
Markdown is supported
0% .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑!
想要评论请 注册