“ASR:2015-08-24”版本间的差异
来自cslt Wiki
（→RNN Rank Task） |
（→financial group） |
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| （3位用户的4个中间修订版本未显示） | |||
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==== Environment ==== | ==== Environment ==== | ||
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==== RNN AM==== | ==== RNN AM==== | ||
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* deliver to mengyuan, xuewei | * deliver to mengyuan, xuewei | ||
:* http://cslt.riit.tsinghua.edu.cn/cgi-bin/cvss/cvss_request.pl?account=zhangzy&step=view_request&cvssid=261 | :* http://cslt.riit.tsinghua.edu.cn/cgi-bin/cvss/cvss_request.pl?account=zhangzy&step=view_request&cvssid=261 | ||
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| − | ===Ivector&Dvector based ASR=== | + | ===Ivector&Dvector based ASR=== |
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* Cluster the speakers to speaker-classes, then using the distance or the posterior-probability as the metric | * Cluster the speakers to speaker-classes, then using the distance or the posterior-probability as the metric | ||
| + | :*hold | ||
* dark-konowlege using i-vector | * dark-konowlege using i-vector | ||
| − | * | + | * RNN ivector |
| − | + | * binary ivector | |
===language vector=== | ===language vector=== | ||
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:* hold | :* hold | ||
* write a paper--zhiyuan | * write a paper--zhiyuan | ||
| + | :*hold | ||
* RNN language vector | * RNN language vector | ||
| − | + | :* hold | |
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| − | :* hold | + | |
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*Read Source Code. | *Read Source Code. | ||
*Attention based QA. | *Attention based QA. | ||
| − | * | + | *Coding. |
====RNN Poem Process==== | ====RNN Poem Process==== | ||
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=financial group= | =financial group= | ||
| − | == | + | ==model research== |
| − | * | + | * RNN |
| − | :* | + | :* online model, update everyday |
| + | :* modify cost function and learning method | ||
| + | :* add more feature | ||
| + | ==rule combination== | ||
| + | * rule analysis | ||
| + | ==basic rule== | ||
| + | * classical tenth model | ||
| − | == | + | ==display== |
| − | * | + | * bug fixed |
| − | :* | + | :* index calculation |
| − | + | :* buy rule fixed | |
| − | :* | + | * document |
| − | + | ==data== | |
| − | + | * data api | |
| − | * | + | * download data |
| − | == | + | |
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2015年8月24日 (一) 08:01的最后版本
目录
- 1 Speech Processing
- 2 Text Processing
- 3 financial group
Speech Processing
AM development
Environment
RNN AM
- train monophone RNN --zhiyuan
- train using large dataset--mengyuan
- write code to tune learning rate--zhiyong
Mic-Array
- hold
- compute EER with kaldi
====Data selection unsupervised learning
- hold
- acoustic feature based submodular using Pingan dataset --zhiyong
- write code to speed up --zhiyong
RNN-DAE(Deep based Auto-Encode-RNN)
- hold
- deliver to mengyuan, xuewei
Ivector&Dvector based ASR
- Cluster the speakers to speaker-classes, then using the distance or the posterior-probability as the metric
- hold
- dark-konowlege using i-vector
- RNN ivector
- binary ivector
language vector
- hold
- train using language vector with the dataset of 1400h_CN + 100h_EN--mengyuan
- hold
- write a paper--zhiyuan
- hold
- RNN language vector
- hold
multi-GPU=
- multi-stream training --Sheng Su
Text Processing
RNN LM
- character-lm rnn(hold)
- lstm+rnn
- check the lstm-rnnlm code about how to Initialize and update learning rate.(hold)
Neural Based Document Classification
- (hold)
RNN Rank Task
- Test.
- Paper: RNN Rank Net.
- (hold)
- Output rank information.
Graph RNN
- Entity path embeded to entity.
- (hold)
RNN Word Segment
- Set bound to word segment.
- (hold)
Seq to Seq(09-15)
- Review papers.
- Reproduce baseline. (08-03 <--> 08-17)
Order representation
- Nested Dropout
- semi-linear --> neural based auto-encoder.
- modify the objective function(hold)
Balance Representation
- Find error signal
Recommendation
- Reproduce baseline.
- LDA matrix dissovle.
- LDA (Text classification & Recommendation System) --> AAAI
RNN based QA
- Read Source Code.
- Attention based QA.
- Coding.
RNN Poem Process
- Seq based BP.
- (hold)
Text Group Intern Project
Buddhist Process
- (hold)
RNN Poem Process
- Done by Haichao yu & Chaoyuan zuo Mentor : Tianyi Luo.
RNN Document Vector
- (hold)
Image Baseline
- Demo Release.
- Paper Report.
- Read CNN Paper.
Text Intuitive Idea
Trace Learning
- (Hold)
Match RNN
- (Hold)
financial group
model research
- RNN
- online model, update everyday
- modify cost function and learning method
- add more feature
rule combination
- rule analysis
basic rule
- classical tenth model
display
- bug fixed
- index calculation
- buy rule fixed
- document
data
- data api
- download data
