This repository accompanies the ACM TOIS paper "What can I cook with these ingredients?" - Understanding cooking-related information needs in conversational search

Overview

beersoup In this repository you find data that has been gathered when conducting in-situ experiments in a conversational cooking setting. These data include transcripts,annotations and code to analyse these data.

When you are here while reading our paper, you might have following questions:

Where can I find the transcripts?

The raw transcripts are located in the transcripts folder. All experiments were conducted in Germany. Therefore, we provide the original german version as well as an english version transcribed with DeepL. Since we put much more effort in the transcription and annotation process compared to our workshop paper (=pilot study), we also provide the annotated data from that paper (see folder transcripts/workshop_paper).

Where is the information need taxonomy?

A visual representation can be found in the annotation folder. InformationNeedTaxonomy.svg is the file you are looking for.

Where is the codebook?

A description of all information needs as well as examples for them are located in the annotation folder. annotation_schema_cookversational_search_german.xlsx is the german version, annotation_schema_cookversational_search.xlsx is the english one. The codebook from our pilot study is located in this folder, too.

Where is the code for the machine learning experiments?

You find code for both the baseline models, the BERT based models and the results in the experiments folder.

Is there a notebook that contains the statistical analyses?

Yes! Statistical Analysis.ipynb in the experimentsfolder is the relevant file.

Where is the CookversationalSearch dataset?

The fully annotated dataset with all information needs, german and english turns (translated with DeepL) is here: annotation/corpus/cookversational_search_dataset

Implementation of QuickDraw - an online game developed by Google, combined with AirGesture - a simple gesture recognition application

QuickDraw - AirGesture Introduction Here is my python source code for QuickDraw - an online game developed by google, combined with AirGesture - a sim

Viet Nguyen 89 Dec 18, 2022
Pytorch implementation for A-NeRF: Articulated Neural Radiance Fields for Learning Human Shape, Appearance, and Pose

A-NeRF: Articulated Neural Radiance Fields for Learning Human Shape, Appearance, and Pose Paper | Website | Data A-NeRF: Articulated Neural Radiance F

Shih-Yang Su 172 Dec 22, 2022
Election Exit Poll Prediction and U.S.A Presidential Speech Analysis using Machine Learning

Machine_Learning Election Exit Poll Prediction and U.S.A Presidential Speech Analysis using Machine Learning This project is based on 2 case-studies:

Avnika Mehta 1 Jan 27, 2022
Very Deep Convolutional Networks for Large-Scale Image Recognition

pytorch-vgg Some scripts to convert the VGG-16 and VGG-19 models [1] from Caffe to PyTorch. The converted models can be used with the PyTorch model zo

Justin Johnson 217 Dec 05, 2022
This is an (re-)implementation of DeepLab-ResNet in TensorFlow for semantic image segmentation on the PASCAL VOC dataset.

DeepLab-ResNet-TensorFlow This is an (re-)implementation of DeepLab-ResNet in TensorFlow for semantic image segmentation on the PASCAL VOC dataset. Up

19 Jan 16, 2022
A script depending on VASP output for calculating Fermi-Softness.

Fermi softness calculation for Vienna Ab initio Simulation Package (VASP) Update 1.1.0: Big update: Rewrote the code. Use Bader atomic division instea

qslin 11 Nov 08, 2022
Speed-Test - You can check your intenet speed using this tool

Speed-Test Tool By Hez_X AVAILABLE ON : Termux & Kali linux & Ubuntu (Linux E

Hez-X 3 Feb 17, 2022
Official repository for the ICLR 2021 paper Evaluating the Disentanglement of Deep Generative Models with Manifold Topology

Official repository for the ICLR 2021 paper Evaluating the Disentanglement of Deep Generative Models with Manifold Topology Sharon Zhou, Eric Zelikman

Stanford Machine Learning Group 34 Nov 16, 2022
HAT: Hierarchical Aggregation Transformers for Person Re-identification

HAT: Hierarchical Aggregation Transformers for Person Re-identification

11 Sep 05, 2022
Multi-Content GAN for Few-Shot Font Style Transfer at CVPR 2018

MC-GAN in PyTorch This is the implementation of the Multi-Content GAN for Few-Shot Font Style Transfer. The code was written by Samaneh Azadi. If you

Samaneh Azadi 422 Dec 04, 2022
Code for Paper "Evidential Softmax for Sparse MultimodalDistributions in Deep Generative Models"

Evidential Softmax for Sparse Multimodal Distributions in Deep Generative Models Abstract Many applications of generative models rely on the marginali

Stanford Intelligent Systems Laboratory 9 Jun 06, 2022
Pytorch implementation of the paper Improving Text-to-Image Synthesis Using Contrastive Learning

T2I_CL This is the official Pytorch implementation of the paper Improving Text-to-Image Synthesis Using Contrastive Learning Requirements Linux Python

42 Dec 31, 2022
A PyTorch implementation of Implicit Q-Learning

IQL-PyTorch This repository houses a minimal PyTorch implementation of Implicit Q-Learning (IQL), an offline reinforcement learning algorithm, along w

Garrett Thomas 30 Dec 12, 2022
Apply a perspective transformation to a raster image inside Inkscape (no need to use an external software such as GIMP or Krita).

Raster Perspective Apply a perspective transformation to bitmap image using the selected path as envelope, without the need to use an external softwar

s.ouchene 19 Dec 22, 2022
Keyword spotting on Arm Cortex-M Microcontrollers

Keyword spotting for Microcontrollers This repository consists of the tensorflow models and training scripts used in the paper: Hello Edge: Keyword sp

Arm Software 1k Dec 30, 2022
Prompts - Read a textfile of prompts and import into anki via ankiconnect

prompts read a textfile of prompts and import into anki via ankiconnect Usage In

Alexander Cobleigh 2 Jul 28, 2022
My tensorflow implementation of "A neural conversational model", a Deep learning based chatbot

Deep Q&A Table of Contents Presentation Installation Running Chatbot Web interface Results Pretrained model Improvements Upgrade Presentation This wor

Conchylicultor 2.9k Dec 28, 2022
Automatically measure the facial Width-To-Height ratio and get facial analysis results provided by Microsoft Azure

fwhr-calc-website This project is to automatically measure the facial Width-To-Height ratio and get facial analysis results provided by Microsoft Azur

SoohyunPark 1 Feb 07, 2022
Official implementation of SynthTIGER (Synthetic Text Image GEneratoR) ICDAR 2021

🐯 SynthTIGER: Synthetic Text Image GEneratoR Official implementation of SynthTIGER | Paper | Datasets Moonbin Yim1, Yoonsik Kim1, Han-cheol Cho1, Sun

Clova AI Research 256 Jan 05, 2023
Learning kernels to maximize the power of MMD tests

Code for the paper "Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy" (arXiv:1611.04488; published at ICLR 2017), by Douga

Danica J. Sutherland 201 Dec 17, 2022