探索说话人识别数据集时要注意的问题

Note:
In the speaker id community the words “train”, “test” and “development”
are used in a different sense from in the speech recognition community. In
speaker-id land, the “development” data is the data you actually use to build
the system; the “training” and “test” data are really both used to test how
well the systme performs. The “training” data is used as enrolment data for a
particular speaker, and the evaluation consists of taking utterances from the
“test” data and having the system decide whether they were uttered by various
training speakers.（来自于kaldi/egs/sre08/v1/README.txt）

短语音对于i-vector的训练是有害的，小于100k的utterence都会被删除。（来自于kaldi/egs/sitw/v1）

enroll集和eval集可能有下面不同：

1. 跨信道，跨设备，跨距离（ios录的？安卓录的？近场录的？远场录的？1个mic录的？n个mic录的？）
2. 性别比例分布极不平衡
3. 采样率一样么？（16k？44.1K？）
4. 音量是否有过大过小情况？
5. 语速是否有过快过慢情况？
6. 时长差异大么？
7. 是否有情绪变化包含在内？
8. 是否有仿冒攻击情况？