Pre-CODE | Exploiting Unsupervised Data for Emotion | Natural Language Processing library
kandi X-RAY | Pre-CODE Summary
kandi X-RAY | Pre-CODE Summary
Emotion Recognition in Conversations (ERC) aims to predict the emotion state of speakers in conversations, which is essentially a text classification task. Unlike the sentence-level text classification problem, the available supervised data for the ERC task is limited, which potentially prevents the models from playing their maximum effect. In this paper, we propose a novel approach to leverage unsupervised conversation data, which is more accessible. Specifically, we propose the Conversation Completion (ConvCom) task, which attempts to select the correct answer from candidate answers to fill a masked utterance in a conversation. Then, we Pre-train a basic COntext-Dependent Encoder (Pre-CODE) on the ConvCom task. Finally, we fine-tune the Pre-CODE on the datasets of ERC. Experimental results demonstrate that pre-training on unsupervised data achieves significant improvement of performance on the ERC datasets, particularly on the minority emotion classes. Conversation Completion (ConvCom) We exploit the self-supervision signal in conversations to construct our pre-training task. Formally, given a conversation, U={ u1, u2, ..., uL }, we mask a target utterance ul as U\u={ ..., ul-1, [mask] , ul+1, ... } to create a question, and try to retrieve the correct utterance ul from the whole training corpus. Since the choice of filling the mask involves all possible utterances, which are countless, formulating the task into a multi-label classification task with softmax is infeasible. We instead simplify the task into a response selection task using negative sampling, which is a variant of noise-contrastive estimation (NCE). To achieve so, we sample N-1 noise utterances elsewhere, along with the target utterance, to form a set of N candidate answers. Then the goal is to select the correct answer, i.e., ul, from the candidate answers to fill the mask, conditioned on the context utterances. We term this task "Conversation Completion", abbreviated as ConvCom. Figure 2 shows an example, where the utterance u4 is masked out from the original conversation and two noise utterances are sampled elsewhere together with u4 to form the candidate answers.
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Top functions reviewed by kandi - BETA
- Emulate the emotrain
- Evaluate the emo evaluation
- Calculates the weight weight of a word
- Compute the class loss
- Build global global global vocabulary
- Adds a sentence to the corpus
- Delete rare words from the corpus
- Build the diadict of emotion dataset
- Train the LM model
- Compute lmeval
- Generate random samples
- Compute the top k elements of a matrix
- Processes an emoset
- Generate index for words and emodata
- Load a pickle file
- Load pretrain
- Load word vectors from file
- Load word vectors from a text file
- Load character vectors
- Load character vector from file
- Compute the word embedding
- Save object to json file
- Loader loader loader
Pre-CODE Key Features
Pre-CODE Examples and Code Snippets
Community Discussions
Trending Discussions on Pre-CODE
QUESTION
Okay, so I'm about to put my Laravel project in production. I tested everything on local host and it works perfectly using Tailwind 3. Yet, when I ran some PHP artisan commands to clear all cache and etc., migrate:fresh my database, and then ran npm run dev, I noticed that Tailwind removed the styles that I used in seeding blogs (I use seed to seed fake blog posts and view how they will look like).
For example I'm using the Typography Tailwind plugin with the utility-class prose and so on. When I ran migrate:fresh and the fake blog post deleted from database, then cleared Laravel cache, and ran npm run dev, I noticed that all the prose styles are being removed from app.css. Of course I don't want that because this should be applied on each and every blog post that I will submit in production.
So how can I stop Tailwind from deleting these styles? I currently have all that I need and I don't want anything else removed.
webpack.mix
...ANSWER
Answered 2022-Mar-13 at 15:00Tailwind will only include the classes that it finds by scanning the files specified in the content array in tailwind.config.js. If you want to include additional classes that are only in your dynamic content, you can safelist those classes in your config. For example:
QUESTION
I found a few web hosting services that look great (e.g. Google Sites, Wix, etc.) but none seem to allow to just upload an HTML file, rather than embed HTML code in a website that was created using the provided web builders. Anyone know of a web hosting service that allows to just upload complete pre-coded HTML files rather than having to go through a web builder? Or is it possible with the two websites I mentioned above? Thank you in advance.
...ANSWER
Answered 2021-Jun-06 at 14:23You can use:
Or if you work with framework such as React or Flask for Python web, you can use https://www.heroku.com/. It's free and you can even host your website through repository on your Github.
QUESTION
Yes, this question has been posted before. Yes I've applied the relevant solutions and ignored the irrelevant ones. I just don't understand what is going on here.
Problem: I make change to my source code by modifying the default return message. I COPY the src tree into my baseImage (multi-stage builds). I build a stagingImage from the baseImage. The baseImage has the code change but the container running the stagingImage returns the pre-code-change message. I've replicated this behavior on MacOs (Catalina) and Amazon Linux 2.
Note that I am doing this manually, i.e. I'm not relying on IDEs and inotfy-s and the like. The only tools involved are the CLI, vim, make and docker(-compose).
Details: I have a Dockerfile that is capable of doing multi-stage builds. Here's the relevant part of the baseImage build:
...ANSWER
Answered 2020-Sep-25 at 00:26Your docker-compose.yml file specifies
QUESTION
I have a noisy square signal which looks like this:
The amplitude is known. To match the complete square, I can create a pattern of the square and apply np.correlate to find where the signal and the pattern maximally overlap. I wanted to apply a similar approach to find the edge, try to correlate with the 2 patterns below:
As the correlation is nothing more than a convolution, this doesn't work. Half the pattern is equal to 0, and the convolution of this half will return 0 no matter the position on the signal; while the other half is equal to -X with X the amplitude. This second half convoluted with the signal will be maximal when the signal amplitude is maximal. On the signal plot, you can observe that the square is not perfect and that the beginning has a slightly larger amplitude. Basically, both correlation leads to a match on the beginning of the square, where the convolution is maximal. The ramp up (end of the square) is not detected.
To avoid this problem, I would like to use a different operation. As I do know the amplitude of the square signal, I can generate a pattern with the correct amplitude, in this case about -0.3. Thus, I would like to take the pattern and slide it across the signal. At each step, I would compute the mean square error and my pattern would match with the signal at the position where the mean square error is minimized. Moreover, I would like to use the same type of setting as for a convolution, 'valid', where the operation is performed only when the 2 arrays fully overlap.
Do you know of an other method; and/or which function, methods I should use? I couldn't find a all-in-one function line np.convolve or np.correlate.
EDIT: Since I couldn't find a pre-coded function in a library, I've coded mine with a while loop. It's pretty inefficient... It's up here on codereview for upgrades.
...ANSWER
Answered 2020-Aug-20 at 09:36Since you have very little noise you can calculte where the signal drastically changes with a loop, for example:
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You can use Pre-CODE like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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