The Rachelbot: Investigation of Persona-Based Chatbots

Project Readme

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Scope And Content	Readme intructions for project code.

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GitHub repository

File Size	4.28 GB
File Format	ZIP Format
Scope And Content	Repository of all code.
Technical Details	Software used: absl-py==0.7.1 asn1crypto=0.24.0=py36_1003 astor==0.7.1 atomicwrites==1.3.0 attrs=19.1.0=py36_1 backcall=0.1.0=py36_0 blas=1.0=mkl bleach=3.1.0=py36_0 blis==0.2.4 boto==2.49.0 boto3==1.9.146 botocore==1.12.146 ca-certificates=2019.1.23=0 ca-certificates=2019.5.15=0 certifi=2019.3.9=py36_0 certifi=2019.3.9=py37_0 cffi=1.12.3=py36h7a1dbc1_0 chardet==3.0.4 click==7.0 cloudpickle==0.8.1 colorama=0.4.1=py36_0 cryptography=2.6.1=py36hb32ad35_0 cudatoolkit=9.0=1 cycler==0.10.0 cycler=0.10.0=py36h009560c_0 cymem==2.0.2 cymem=2.0.2=py36h74a9793_0 cython==0.29.7 cython-blis=0.2.4=py36hfa6e2cd_0 dask==1.2.0 decorator==4.4.0 decorator=4.4.0=py36_1 defusedxml=0.6.0=py_0 docutils==0.14 en-core-web-sm==2.1.0 entrypoints=0.3=py36_0 essential-generators==0.9.2 flask==1.0.3 flask-cors==3.0.8 freetype=2.9.1=ha9979f8_1 ftfy==5.5.1 funcy==1.12 future==0.17.1 gast==0.2.2 gensim==3.7.3 grpcio==1.20.1 h5py==2.9.0 icc_rt=2019.0.0=h0cc432a_1 icu=58.2=ha66f8fd_1 idna==2.8 importlib-metadata==0.18 intel-openmp=2019.3=203 ipykernel=5.1.0=py36h39e3cac_0 ipython_genutils=0.2.0=py36h3c5d0ee_0 ipython=7.5.0=py36h39e3cac_0 ipywidgets=7.4.2=py36_0 itsdangerous==1.1.0 jedi=0.13.3=py36_0 jinja2=2.10.1=py36_0 jmespath==0.9.4 joblib==0.13.2 jpeg=9b=hb83a4c4_2 jsonschema==2.6.0 jsonschema=3.0.0a3=py36_1000 jupyter_client=5.2.4=py36_0 jupyter_console=6.0.0=py36_0 jupyter_core=4.4.0=py36_0 jupyter=1.0.0=py36_7 keras-applications==1.0.7 keras-preprocessing==1.0.9 kiwisolver==1.1.0 kiwisolver=1.1.0=py36ha925a31_0 libpng=1.6.37=h2a8f88b_0 libsodium=1.0.16=h9d3ae62_0 libtiff=4.0.10=hb898794_2 ludwig==0.1.1 m2w64-gcc-libgfortran=5.3.0=6 m2w64-gcc-libs=5.3.0=7 m2w64-gcc-libs-core=5.3.0=7 m2w64-gmp=6.1.0=2 m2w64-libwinpthread-git=5.0.0.4634.697f757=2 markdown==3.1 markupsafe=1.1.1=py36he774522_0 matplotlib==3.0.3 matplotlib=3.1.0=py36hc8f65d3_0 mistune=0.8.4=py36he774522_0 mkl_fft=1.0.12=py36h14836fe_0 mkl_random=1.0.2=py36h343c172_0 mkl=2019.3=203 mock==2.0.0 mock==3.0.5 more-itertools==7.0.0 msys2-conda-epoch=20160418=1 murmurhash==1.0.2 murmurhash=1.0.0=py36h6538335_0 nbconvert=5.5.0=py_0 nbformat=4.4.0=py36h3a5bc1b_0 networkx==2.3 ninja=1.9.0=py36h74a9793_0 nltk==3.4.3 notebook=5.7.8=py36_0 numexpr==2.6.9 numpy==1.16.3 numpy=1.16.3=py36h19fb1c0_0 numpy-base=1.16.3=py36hc3f5095_0 olefile=0.46=py36_0 openssl=1.1.1b=he774522_1 openssl=1.1.1c=he774522_1 packaging==19.0 pandas==0.24.2 pandoc=2.2.3.2=0 pandocfilters=1.4.2=py36_1 parso=0.4.0=py_0 pbr==5.1.3 pickleshare=0.7.5=py36_0 pillow==6.0.0 pillow=6.0.0=py36hdc69c19_0 pip=19.0.3=py37_0 pip=19.1.1=py36_0 plac==0.9.6 plac=0.9.6=py_1 pluggy==0.12.0 preshed==2.0.1 preshed=2.0.1=py36h33f27b4_0 prometheus_client=0.6.0=py36_0 prompt_toolkit=2.0.9=py36_0 protobuf==3.7.1 py==1.8.0 pycparser=2.19=py36_0 pygments=2.4.0=py_0 pyldavis==2.1.2 pyopenssl=19.0.0=py36_0 pyparsing==2.4.0 pyparsing=2.4.0=py_0 pyqt=5.9.2=py36h6538335_2 pyrsistent=0.14.11=py36he774522_0 pysocks=1.7.0=py36_0 pytest==4.6.3 python=2.7 python=3.6 python=3.6.8=h9f7ef89_7 python=3.7 python=3.7.3=h8c8aaf0_0 python-dateutil==2.8.0 python-dateutil=2.8.0=py36_0 pytorch=1.1.0=py3.6_cuda90_cudnn7_1 pytorch-ignite==0.2.0 pytorch-pretrained-bert==0.6.2 pytz==2019.1 pytz=2019.1=py_0 pywavelets==1.0.3 pywinpty=0.5.5=py36_1000 pyyaml==5.1 pyzmq=18.0.0=py36ha925a31_0 qt=5.9.7=vc14h73c81de_0 qtconsole=4.4.4=py_0 regex==2019.04.14 requests==2.21.0 requests=2.21.0=py36_1000 s3transfer==0.2.0 scikit-image==0.14.2 scikit-learn==0.20.3 scipy==1.2.1 scipy==1.3.0 seaborn==0.9.0 send2trash=1.5.0=py36_0 setuptools=41.0.0=py37_0 setuptools=41.0.1=py36_0 sip=4.19.8=py36h6538335_0 six==1.12.0 six=1.12.0=py36_0 smart-open==1.8.4 spacy==2.1.3 spacy=2.1.4=py36he980bc4_0 sqlite=3.28.0=he774522_0 srsly==0.0.5 srsly=0.0.5=py36h6538335_0 tabulate==0.8.3 tensorboard==1.13.1 tensorboardx==1.6 tensorflow==1.13.1 tensorflow-estimator==1.13.0 tensorflow-gpu==1.13.1 termcolor==1.1.0 terminado=0.8.2=py36_0 testpath=0.4.2=py36_0 thinc==7.0.4 thinc=7.0.4=py36he980bc4_0 tk=8.6.8=hfa6e2cd_0 toolz==0.9.0 torchvision=0.2.2=py_3 tornado=6.0.2=py36he774522_0 tqdm==4.31.1 tqdm=4.31.1=py_0 traitlets=4.3.2=py36h096827d_0 urllib3==1.24.2 urllib3==1.24.3 vc=14.1=h0510ff6_4 vs2015_runtime=14.15.26706=h3a45250_0 vs2015_runtime=14.15.26706=h3a45250_4 wasabi==0.2.1 wasabi=0.2.2=py_0 wcwidth=0.1.7=py36h3d5aa90_0 webencodings=0.5.1=py36_1 werkzeug==0.15.2 wheel=0.33.1=py37_0 wheel=0.33.2=py36_0 widgetsnbextension=3.4.2=py36_0 win_inet_pton=1.1.0=py36_0 wincertstore=0.2=py36h7fe50ca_0 wincertstore=0.2=py37_0 winpty=0.4.3=4 wordcloud==1.5.0 xz=5.2.4=h2fa13f4_4 zeromq=4.3.1=h33f27b4_3 zipp==0.5.1 zlib=1.2.11=h62dcd97_3 zstd=1.3.7=h508b16e_0

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Final report

File Size	2.51 MB
File Format	Portable Document Format
Scope And Content	Final report of the capstone project.

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Raw data

File Size	14.3 MB
File Format	Plain text
Scope And Content	Scripts of all Friends episodes.

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Output data

File Size	457 MB
File Format	Binary File
Scope And Content	Model containing all parameter data to execute rachelbot.
Technical Details	Software used: asn1crypto=0.24.0=py36_1003 attrs=19.1.0=py36_1 backcall=0.1.0=py36_0 blas=1.0=mkl bleach=3.1.0=py36_0 ca-certificates=2019.5.15=0 certifi=2019.3.9=py36_0 cffi=1.12.3=py36h7a1dbc1_0 colorama=0.4.1=py36_0 cryptography=2.6.1=py36hb32ad35_0 cudatoolkit=9.0=1 cycler=0.10.0=py36h009560c_0 cymem=2.0.2=py36h74a9793_0 cython-blis=0.2.4=py36hfa6e2cd_0 decorator=4.4.0=py36_1 defusedxml=0.6.0=py_0 entrypoints=0.3=py36_0 freetype=2.9.1=ha9979f8_1 icc_rt=2019.0.0=h0cc432a_1 icu=58.2=ha66f8fd_1 intel-openmp=2019.3=203 ipykernel=5.1.0=py36h39e3cac_0 ipython=7.5.0=py36h39e3cac_0 ipython_genutils=0.2.0=py36h3c5d0ee_0 ipywidgets=7.4.2=py36_0 jedi=0.13.3=py36_0 jinja2=2.10.1=py36_0 jpeg=9b=hb83a4c4_2 jsonschema=3.0.0a3=py36_1000 jupyter=1.0.0=py36_7 jupyter_client=5.2.4=py36_0 jupyter_console=6.0.0=py36_0 jupyter_core=4.4.0=py36_0 kiwisolver=1.1.0=py36ha925a31_0 libpng=1.6.37=h2a8f88b_0 libsodium=1.0.16=h9d3ae62_0 libtiff=4.0.10=hb898794_2 m2w64-gcc-libgfortran=5.3.0=6 m2w64-gcc-libs=5.3.0=7 m2w64-gcc-libs-core=5.3.0=7 m2w64-gmp=6.1.0=2 m2w64-libwinpthread-git=5.0.0.4634.697f757=2 markupsafe=1.1.1=py36he774522_0 matplotlib=3.1.0=py36hc8f65d3_0 mistune=0.8.4=py36he774522_0 mkl=2019.3=203 mkl_fft=1.0.12=py36h14836fe_0 mkl_random=1.0.2=py36h343c172_0 msys2-conda-epoch=20160418=1 murmurhash=1.0.0=py36h6538335_0 nbconvert=5.5.0=py_0 nbformat=4.4.0=py36h3a5bc1b_0 ninja=1.9.0=py36h74a9793_0 notebook=5.7.8=py36_0 numpy=1.16.3=py36h19fb1c0_0 numpy-base=1.16.3=py36hc3f5095_0 olefile=0.46=py36_0 openssl=1.1.1c=he774522_1 pandoc=2.2.3.2=0 pandocfilters=1.4.2=py36_1 parso=0.4.0=py_0 pickleshare=0.7.5=py36_0 pillow=6.0.0=py36hdc69c19_0 pip=19.1.1=py36_0 plac=0.9.6=py_1 preshed=2.0.1=py36h33f27b4_0 prometheus_client=0.6.0=py36_0 prompt_toolkit=2.0.9=py36_0 pycparser=2.19=py36_0 pygments=2.4.0=py_0 pyopenssl=19.0.0=py36_0 pyparsing=2.4.0=py_0 pyqt=5.9.2=py36h6538335_2 pyrsistent=0.14.11=py36he774522_0 pysocks=1.7.0=py36_0 python=3.6.8=h9f7ef89_7 python-dateutil=2.8.0=py36_0 pytorch=1.1.0=py3.6_cuda90_cudnn7_1 pytz=2019.1=py_0 pywinpty=0.5.5=py36_1000 pyzmq=18.0.0=py36ha925a31_0 qt=5.9.7=vc14h73c81de_0 qtconsole=4.4.4=py_0 requests=2.21.0=py36_1000 send2trash=1.5.0=py36_0 setuptools=41.0.1=py36_0 sip=4.19.8=py36h6538335_0 six=1.12.0=py36_0 spacy=2.1.4=py36he980bc4_0 sqlite=3.28.0=he774522_0 srsly=0.0.5=py36h6538335_0 terminado=0.8.2=py36_0 testpath=0.4.2=py36_0 thinc=7.0.4=py36he980bc4_0 tk=8.6.8=hfa6e2cd_0 torchvision=0.2.2=py_3 tornado=6.0.2=py36he774522_0 tqdm=4.31.1=py_0 traitlets=4.3.2=py36h096827d_0 vc=14.1=h0510ff6_4 vs2015_runtime=14.15.26706=h3a45250_4 wasabi=0.2.2=py_0 wcwidth=0.1.7=py36h3d5aa90_0 webencodings=0.5.1=py36_1 wheel=0.33.2=py36_0 widgetsnbextension=3.4.2=py36_0 win_inet_pton=1.1.0=py36_0 wincertstore=0.2=py36h7fe50ca_0 winpty=0.4.3=4 xz=5.2.4=h2fa13f4_4 zeromq=4.3.1=h33f27b4_3 zlib=1.2.11=h62dcd97_3 zstd=1.3.7=h508b16e_0 absl-py==0.7.1 astor==0.7.1 atomicwrites==1.3.0 boto==2.49.0 boto3==1.9.146 botocore==1.12.146 chardet==3.0.4 click==7.0 docutils==0.14 en-core-web-sm==2.1.0 essential-generators==0.9.2 flask==1.0.3 flask-cors==3.0.8 ftfy==5.5.1 funcy==1.12 future==0.17.1 gast==0.2.2 gensim==3.7.3 grpcio==1.20.1 h5py==2.9.0 idna==2.8 importlib-metadata==0.18 itsdangerous==1.1.0 jmespath==0.9.4 joblib==0.13.2 keras-applications==1.0.7 keras-preprocessing==1.0.9 markdown==3.1 mock==3.0.5 more-itertools==7.0.0 nltk==3.4.3 numexpr==2.6.9 packaging==19.0 pandas==0.24.2 pluggy==0.12.0 protobuf==3.7.1 py==1.8.0 pyldavis==2.1.2 pytest==4.6.3 pytorch-ignite==0.2.0 pytorch-pretrained-bert==0.6.2 regex==2019.04.14 s3transfer==0.2.0 scipy==1.3.0 smart-open==1.8.4 tensorboard==1.13.1 tensorboardx==1.6 tensorflow==1.13.1 tensorflow-estimator==1.13.0 termcolor==1.1.0 urllib3==1.24.3 werkzeug==0.15.2 wordcloud==1.5.0 zipp==0.5.1

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Collection

Data Science & Engineering Master of Advanced Study (DSE MAS) Capstone Projects

Cite This Work

Orona, Alexander J.; Malasky, Martin; Fisher, Matthew; Gupta, Amarnath (2019). The Rachelbot: Investigation of Persona-Based Chatbots. In Data Science & Engineering Master of Advanced Study (DSE MAS) Capstone Projects. UC San Diego Library Digital Collections. https://doi.org/10.6075/J0RV0M1S

Description

Creating agents that closely mimic human conversational patterns has been a major goal of research and industry for decades. Recent advances in recurrent and transformer deep learning architectures have made significant progress toward open domain chatbots that capture the highly contextual nature of conversations. In the last several years, researchers have turned to personas as one way of improving dialogue quality.

In this project, current methods for building persona-based conversational agents are tested using a chatbot of a popular character (Rachel from the TV show Friends). Our aim is to: 1) deliver an engaging Friends experience to fans of the show, 2) assess chatbot deep learning architectures, and 3) establish the limits of contemporary approaches and potential areas for additional research.

Creation Date

2019

Date Issued

2019

Authors

Advisors

Series

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Identifier

Doi: https://doi.org/10.6075/J0RV0M1S

Related Resource

Source data

Transcript retrieved from Eric Aasen (2004), Crazy for Friends: http://www.livesinabox.com/friends/scripts.shtml

License

Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Public License

Rights Holder

Orona, Alexander J.; Malasky, Martin

Copyright

Under copyright (US)

Use: This work is available from the UC San Diego Library. This digital copy of the work is intended to support research, teaching, and private study.

Constraint(s) on Use: This work is protected by the U.S. Copyright Law (Title 17, U.S.C.). Use of this work beyond that allowed by "fair use" or any license applied to this work requires written permission of the copyright holder(s). Responsibility for obtaining permissions and any use and distribution of this work rests exclusively with the user and not the UC San Diego Library. Inquiries can be made to the UC San Diego Library program having custody of the work.

Digital Object Made Available By

Research Data Curation Program, UC San Diego, La Jolla, 92093-0175 (https://lib.ucsd.edu/rdcp)

Last Modified

2022-11-28