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Disambiguation – Linking Data Science and Engineering | NLP Summit 2020
Get your Free Spark NLP and Spark OCR Free Trial: https://www.johnsnowlabs.com/spark-nlp-try-free/
Register for NLP Summit 2021: https://www.nlpsummit.org/2021-events/
Watch all NLP Summit 2020 sessions: https://www.nlpsummit.org/
Disambiguation or Entity Linking is the assignment of a knowledge base identifier (Wikidata, Wikipedia) to a named entity. Our goal was to improve an MVP model by adding newly created knowledge while maintaining competitive F1 scores.
Taking an entity linking model from MVP into production in a spaCy-native pipeline architecture posed several data science and engineering challenges, such as hyperparameter estimation and knowledge enhancement, which we addressed by taking advantage of the engineering tools Docker and Kubernetes to semi-automate training as a...
published: 07 Jan 2021
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chess king sacrifice
Credits to: Chessbase India
published: 01 Dec 2020
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Laminar Flow DISAMBIGUATION
Captain Disillusion gets his hands wet with some experiments, and lets you watch.
Please consider supporting my videos on: http://www.patreon.com/CaptainDisillusion
published: 14 Feb 2019
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Entity Disambiguation with Extreme Multi label Ranking
Jyun-Yu Jiang, Amazon Search, Palo Alto, USA
published: 23 Jul 2024
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🖋 Word Sense Disambiguation in Colab using KerasNLP.
💻 Colab : https://colab.research.google.com/drive/18f_zHHAsLw5wTvwIsqbbCt0vHUo3eXkh#scrollTo=ucdAmePvir2e
🛠️ Project GitHub : https://github.com/aalgirdas/wordnet_onto
📝 Research paper: https://www.mdpi.com/2076-3417/14/13/5550
published: 13 May 2024
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Towards Racially Unbiased Skin Tone Estimation via Scene Disambiguation
Virtual facial avatars will play an increasingly important role in immersive communication, games and the metaverse, and it is therefore critical that they be inclusive. This requires accurate recovery of the albedo, regardless of age, sex, or ethnicity. While significant progress has been made on estimating 3D facial geometry, appearance estimation has received less attention. The task is fundamentally ambiguous because the observed color is a function of albedo and lighting, both of which are unknown. We find that current methods are biased towards light skin tones due to (1) strongly biased priors that prefer lighter pigmentation and (2) algorithmic solutions that disregard the light/albedo ambiguity. To address this, we propose a new evaluation dataset (FAIR) and an algorithm (TRUST) t...
published: 27 Oct 2022
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[Sugar] Disambiguation
Hello, my darlings!
It has been a long three months since I've last uploaded something but I've finally had the time to sit down and make a new cover!
This cover has been in the works for a very long time now I originally recording this back in November.
I really like this song simply by how it sounded but upon looking further into it, it has a deeper meaning and I really enjoy it. I hope you enjoy it as well! I want to thank everyone who has worked on this with me and I couldn't be happier!
--------------------------------
Song: 曖昧さ回避 Disambiguation
Composer: Police Piccadilly
English: XxAlelokkxX (http://tinyurl.com/l7po75m)
Mixer: Kirby503 (twitter.com/kirby503)
Illustrator: ZaikoUC (twitter.com/zaikouc)
Vocals/Vid: Sugarlat
Download the MP3 : http://tinyurl.com/l9kogsp
Follow me on ...
published: 10 Apr 2017
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Word Sense Disambiguation
Material based on Jurafsky and Martin (2019): https://web.stanford.edu/~jurafsky/slp3/
Slides: http://www.natalieparde.com/teaching/cs_421_fall2020/Word%20Sense%20Disambiguation.pdf
Twitter: @NatalieParde
published: 28 Dec 2020
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Improving Polyphone Disambiguation for Mandarin Chinese by Combining Mix-pooling Strategy and Wi...
Title: Improving Polyphone Disambiguation for Mandarin Chinese by Combining Mix-pooling Strategy and Window-based Attention - (longer introduction)
Authors: Junjie Li (Ping An Technology, China), Zhiyu Zhang (National Tsing Hua University, Taiwan), Minchuan Chen (Ping An Technology, China), Jun Ma (Ping An Technology, China), Shaojun Wang (Ping An Technology, China), Jing Xiao (Ping An Technology, China)
Category: Speech Synthesis: Linguistic processing, paradigms and other topics
Abstract: In this paper, we propose a novel system based on word-level features and window-based attention for polyphone disambiguation, which is a fundamental task for Grapheme-to-phoneme (G2P) conversion of Mandarin Chinese. The framework aims to combine a pre-trained language model with explicit word-level ...
published: 03 Feb 2022
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[CVPR 2024] From Correspondences to Pose: Non-minimal Relative Pose without Disambiguation
From Correspondences to Pose: Non-minimal Certifiably Optimal Relative Pose without Disambiguation
Authors: Javier Tirado-Garín and Javier Civera
Project Page: https://javrtg.github.io/C2P
Paper: https://arxiv.org/abs/2312.05995
Code: https://github.com/javrtg/C2P
Abstract:
Estimating the relative camera pose from n ≥ 5 correspondences between two calibrated views is a fundamental task in computer vision. This process typically involves two stages: 1) estimating the essential matrix between the views, and 2) disambiguating among the four candidate relative poses that satisfy the epipolar geometry. In this paper, we demonstrate a novel approach that, for the first time, bypasses the second stage. Specifically, we show that it is possible to directly estimate the correct relative camera po...
published: 05 Jun 2024
29:09
Disambiguation – Linking Data Science and Engineering | NLP Summit 2020
Get your Free Spark NLP and Spark OCR Free Trial: https://www.johnsnowlabs.com/spark-nlp-try-free/
Register for NLP Summit 2021: https://www.nlpsummit.org/2021...
Get your Free Spark NLP and Spark OCR Free Trial: https://www.johnsnowlabs.com/spark-nlp-try-free/
Register for NLP Summit 2021: https://www.nlpsummit.org/2021-events/
Watch all NLP Summit 2020 sessions: https://www.nlpsummit.org/
Disambiguation or Entity Linking is the assignment of a knowledge base identifier (Wikidata, Wikipedia) to a named entity. Our goal was to improve an MVP model by adding newly created knowledge while maintaining competitive F1 scores.
Taking an entity linking model from MVP into production in a spaCy-native pipeline architecture posed several data science and engineering challenges, such as hyperparameter estimation and knowledge enhancement, which we addressed by taking advantage of the engineering tools Docker and Kubernetes to semi-automate training as an on-demand job.
We also discuss some of our learnings and process improvements that were needed to strike a balance between data science goals and engineering constraints and present our current work on improving performance through BERT-embedding based contextual similarity.
https://wn.com/Disambiguation_–_Linking_Data_Science_And_Engineering_|_Nlp_Summit_2020
Get your Free Spark NLP and Spark OCR Free Trial: https://www.johnsnowlabs.com/spark-nlp-try-free/
Register for NLP Summit 2021: https://www.nlpsummit.org/2021-events/
Watch all NLP Summit 2020 sessions: https://www.nlpsummit.org/
Disambiguation or Entity Linking is the assignment of a knowledge base identifier (Wikidata, Wikipedia) to a named entity. Our goal was to improve an MVP model by adding newly created knowledge while maintaining competitive F1 scores.
Taking an entity linking model from MVP into production in a spaCy-native pipeline architecture posed several data science and engineering challenges, such as hyperparameter estimation and knowledge enhancement, which we addressed by taking advantage of the engineering tools Docker and Kubernetes to semi-automate training as an on-demand job.
We also discuss some of our learnings and process improvements that were needed to strike a balance between data science goals and engineering constraints and present our current work on improving performance through BERT-embedding based contextual similarity.
- published: 07 Jan 2021
- views: 545
9:18
Laminar Flow DISAMBIGUATION
Captain Disillusion gets his hands wet with some experiments, and lets you watch.
Please consider supporting my videos on: http://www.patreon.com/CaptainDisill...
Captain Disillusion gets his hands wet with some experiments, and lets you watch.
Please consider supporting my videos on: http://www.patreon.com/CaptainDisillusion
https://wn.com/Laminar_Flow_Disambiguation
Captain Disillusion gets his hands wet with some experiments, and lets you watch.
Please consider supporting my videos on: http://www.patreon.com/CaptainDisillusion
- published: 14 Feb 2019
- views: 9903281
11:39
🖋 Word Sense Disambiguation in Colab using KerasNLP.
💻 Colab : https://colab.research.google.com/drive/18f_zHHAsLw5wTvwIsqbbCt0vHUo3eXkh#scrollTo=ucdAmePvir2e
🛠️ Project GitHub : https://github.com/aalgirdas/word...
💻 Colab : https://colab.research.google.com/drive/18f_zHHAsLw5wTvwIsqbbCt0vHUo3eXkh#scrollTo=ucdAmePvir2e
🛠️ Project GitHub : https://github.com/aalgirdas/wordnet_onto
📝 Research paper: https://www.mdpi.com/2076-3417/14/13/5550
https://wn.com/🖋_Word_Sense_Disambiguation_In_Colab_Using_Kerasnlp.
💻 Colab : https://colab.research.google.com/drive/18f_zHHAsLw5wTvwIsqbbCt0vHUo3eXkh#scrollTo=ucdAmePvir2e
🛠️ Project GitHub : https://github.com/aalgirdas/wordnet_onto
📝 Research paper: https://www.mdpi.com/2076-3417/14/13/5550
- published: 13 May 2024
- views: 147
4:54
Towards Racially Unbiased Skin Tone Estimation via Scene Disambiguation
Virtual facial avatars will play an increasingly important role in immersive communication, games and the metaverse, and it is therefore critical that they be i...
Virtual facial avatars will play an increasingly important role in immersive communication, games and the metaverse, and it is therefore critical that they be inclusive. This requires accurate recovery of the albedo, regardless of age, sex, or ethnicity. While significant progress has been made on estimating 3D facial geometry, appearance estimation has received less attention. The task is fundamentally ambiguous because the observed color is a function of albedo and lighting, both of which are unknown. We find that current methods are biased towards light skin tones due to (1) strongly biased priors that prefer lighter pigmentation and (2) algorithmic solutions that disregard the light/albedo ambiguity. To address this, we propose a new evaluation dataset (FAIR) and an algorithm (TRUST) to improve albedo estimation and, hence, fairness. Specifically, we create the first facial albedo evaluation benchmark where subjects are balanced in terms of skin color, and measure accuracy using the Individual Typology Angle (ITA) metric. We then address the light/albedo ambiguity by building on a key observation: the image of the full scene –as opposed to a cropped image of the face– contains important information about lighting that can be used for disambiguation. TRUST regresses facial albedo by conditioning on both the face region and a global illumination signal obtained from the scene image. Our experimental results show significant improvement compared to state- of-the-art methods on albedo estimation, both in terms of accuracy and fairness. The evaluation benchmark and code are available for research purposes at https://trust.is.tue.mpg.de.
PDF: https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136730072.pdf
Project: https://trust.is.tue.mpg.de/index.html
Code: https://github.com/HavenFeng/TRUST
Dataset: https://trust.is.tue.mpg.de/login.php
Reference:
@inproceedings{TRUST:ECCV2022,
title = {Towards Racially Unbiased Skin Tone Estimation via Scene Disambiguation},
author = {Feng, Haiwen and Bolkart, Timo and Tesch, Joachim and Black, Michael J. and Abrevaya, Victoria},
booktitle = {European Conference on Computer Vision (ECCV)},
publisher = {Springer International Publishing},
month = oct,
year = {2022},
doi = {},
month_numeric = {10}
}
https://wn.com/Towards_Racially_Unbiased_Skin_Tone_Estimation_Via_Scene_Disambiguation
Virtual facial avatars will play an increasingly important role in immersive communication, games and the metaverse, and it is therefore critical that they be inclusive. This requires accurate recovery of the albedo, regardless of age, sex, or ethnicity. While significant progress has been made on estimating 3D facial geometry, appearance estimation has received less attention. The task is fundamentally ambiguous because the observed color is a function of albedo and lighting, both of which are unknown. We find that current methods are biased towards light skin tones due to (1) strongly biased priors that prefer lighter pigmentation and (2) algorithmic solutions that disregard the light/albedo ambiguity. To address this, we propose a new evaluation dataset (FAIR) and an algorithm (TRUST) to improve albedo estimation and, hence, fairness. Specifically, we create the first facial albedo evaluation benchmark where subjects are balanced in terms of skin color, and measure accuracy using the Individual Typology Angle (ITA) metric. We then address the light/albedo ambiguity by building on a key observation: the image of the full scene –as opposed to a cropped image of the face– contains important information about lighting that can be used for disambiguation. TRUST regresses facial albedo by conditioning on both the face region and a global illumination signal obtained from the scene image. Our experimental results show significant improvement compared to state- of-the-art methods on albedo estimation, both in terms of accuracy and fairness. The evaluation benchmark and code are available for research purposes at https://trust.is.tue.mpg.de.
PDF: https://www.ecva.net/papers/eccv_2022/papers_ECCV/papers/136730072.pdf
Project: https://trust.is.tue.mpg.de/index.html
Code: https://github.com/HavenFeng/TRUST
Dataset: https://trust.is.tue.mpg.de/login.php
Reference:
@inproceedings{TRUST:ECCV2022,
title = {Towards Racially Unbiased Skin Tone Estimation via Scene Disambiguation},
author = {Feng, Haiwen and Bolkart, Timo and Tesch, Joachim and Black, Michael J. and Abrevaya, Victoria},
booktitle = {European Conference on Computer Vision (ECCV)},
publisher = {Springer International Publishing},
month = oct,
year = {2022},
doi = {},
month_numeric = {10}
}
- published: 27 Oct 2022
- views: 1087
3:28
[Sugar] Disambiguation
Hello, my darlings!
It has been a long three months since I've last uploaded something but I've finally had the time to sit down and make a new cover!
This cove...
Hello, my darlings!
It has been a long three months since I've last uploaded something but I've finally had the time to sit down and make a new cover!
This cover has been in the works for a very long time now I originally recording this back in November.
I really like this song simply by how it sounded but upon looking further into it, it has a deeper meaning and I really enjoy it. I hope you enjoy it as well! I want to thank everyone who has worked on this with me and I couldn't be happier!
--------------------------------
Song: 曖昧さ回避 Disambiguation
Composer: Police Piccadilly
English: XxAlelokkxX (http://tinyurl.com/l7po75m)
Mixer: Kirby503 (twitter.com/kirby503)
Illustrator: ZaikoUC (twitter.com/zaikouc)
Vocals/Vid: Sugarlat
Download the MP3 : http://tinyurl.com/l9kogsp
Follow me on Twitter : https://twitter.com/#!/Sugarlat
Like me on Facebook : http://www.facebook.com/sugarlat
Sing w me on Smule:https://www.smule.com/Sugarlat
-----------------------------------------------------
https://wn.com/Sugar_Disambiguation
Hello, my darlings!
It has been a long three months since I've last uploaded something but I've finally had the time to sit down and make a new cover!
This cover has been in the works for a very long time now I originally recording this back in November.
I really like this song simply by how it sounded but upon looking further into it, it has a deeper meaning and I really enjoy it. I hope you enjoy it as well! I want to thank everyone who has worked on this with me and I couldn't be happier!
--------------------------------
Song: 曖昧さ回避 Disambiguation
Composer: Police Piccadilly
English: XxAlelokkxX (http://tinyurl.com/l7po75m)
Mixer: Kirby503 (twitter.com/kirby503)
Illustrator: ZaikoUC (twitter.com/zaikouc)
Vocals/Vid: Sugarlat
Download the MP3 : http://tinyurl.com/l9kogsp
Follow me on Twitter : https://twitter.com/#!/Sugarlat
Like me on Facebook : http://www.facebook.com/sugarlat
Sing w me on Smule:https://www.smule.com/Sugarlat
-----------------------------------------------------
- published: 10 Apr 2017
- views: 258
6:59
Word Sense Disambiguation
Material based on Jurafsky and Martin (2019): https://web.stanford.edu/~jurafsky/slp3/
Slides: http://www.natalieparde.com/teaching/cs_421_fall2020/Word%20Sens...
Material based on Jurafsky and Martin (2019): https://web.stanford.edu/~jurafsky/slp3/
Slides: http://www.natalieparde.com/teaching/cs_421_fall2020/Word%20Sense%20Disambiguation.pdf
Twitter: @NatalieParde
https://wn.com/Word_Sense_Disambiguation
Material based on Jurafsky and Martin (2019): https://web.stanford.edu/~jurafsky/slp3/
Slides: http://www.natalieparde.com/teaching/cs_421_fall2020/Word%20Sense%20Disambiguation.pdf
Twitter: @NatalieParde
- published: 28 Dec 2020
- views: 9995
14:55
Improving Polyphone Disambiguation for Mandarin Chinese by Combining Mix-pooling Strategy and Wi...
Title: Improving Polyphone Disambiguation for Mandarin Chinese by Combining Mix-pooling Strategy and Window-based Attention - (longer introduction)
Authors: Ju...
Title: Improving Polyphone Disambiguation for Mandarin Chinese by Combining Mix-pooling Strategy and Window-based Attention - (longer introduction)
Authors: Junjie Li (Ping An Technology, China), Zhiyu Zhang (National Tsing Hua University, Taiwan), Minchuan Chen (Ping An Technology, China), Jun Ma (Ping An Technology, China), Shaojun Wang (Ping An Technology, China), Jing Xiao (Ping An Technology, China)
Category: Speech Synthesis: Linguistic processing, paradigms and other topics
Abstract: In this paper, we propose a novel system based on word-level features and window-based attention for polyphone disambiguation, which is a fundamental task for Grapheme-to-phoneme (G2P) conversion of Mandarin Chinese. The framework aims to combine a pre-trained language model with explicit word-level information in order to get meaningful context extraction. Particularly, we employ a pre-trained bidirectional encoder from Transformers (BERT) model to extract character-level features, and an external Chinese word segmentation (CWS) tool is used to obtain the word units. We adopt a mixed pooling mechanism to convert character-level features into word-level features based on the segmentation results. A window-based attention module is utilized to incorporate contextual word-level features for the polyphonic characters. Experimental results show that our method achieves an accuracy of 99.06% on an open benchmark dataset for Mandarin Chinese polyphone disambiguation, which outperforms the baseline systems.
For more details and PDF version of the paper visit: https://www.isca-speech.org/archive/interspeech_2021/li21n_interspeech.html
d04s07t04lng
https://wn.com/Improving_Polyphone_Disambiguation_For_Mandarin_Chinese_By_Combining_Mix_Pooling_Strategy_And_Wi...
Title: Improving Polyphone Disambiguation for Mandarin Chinese by Combining Mix-pooling Strategy and Window-based Attention - (longer introduction)
Authors: Junjie Li (Ping An Technology, China), Zhiyu Zhang (National Tsing Hua University, Taiwan), Minchuan Chen (Ping An Technology, China), Jun Ma (Ping An Technology, China), Shaojun Wang (Ping An Technology, China), Jing Xiao (Ping An Technology, China)
Category: Speech Synthesis: Linguistic processing, paradigms and other topics
Abstract: In this paper, we propose a novel system based on word-level features and window-based attention for polyphone disambiguation, which is a fundamental task for Grapheme-to-phoneme (G2P) conversion of Mandarin Chinese. The framework aims to combine a pre-trained language model with explicit word-level information in order to get meaningful context extraction. Particularly, we employ a pre-trained bidirectional encoder from Transformers (BERT) model to extract character-level features, and an external Chinese word segmentation (CWS) tool is used to obtain the word units. We adopt a mixed pooling mechanism to convert character-level features into word-level features based on the segmentation results. A window-based attention module is utilized to incorporate contextual word-level features for the polyphonic characters. Experimental results show that our method achieves an accuracy of 99.06% on an open benchmark dataset for Mandarin Chinese polyphone disambiguation, which outperforms the baseline systems.
For more details and PDF version of the paper visit: https://www.isca-speech.org/archive/interspeech_2021/li21n_interspeech.html
d04s07t04lng
- published: 03 Feb 2022
- views: 10
4:59
[CVPR 2024] From Correspondences to Pose: Non-minimal Relative Pose without Disambiguation
From Correspondences to Pose: Non-minimal Certifiably Optimal Relative Pose without Disambiguation
Authors: Javier Tirado-Garín and Javier Civera
Project Page:...
From Correspondences to Pose: Non-minimal Certifiably Optimal Relative Pose without Disambiguation
Authors: Javier Tirado-Garín and Javier Civera
Project Page: https://javrtg.github.io/C2P
Paper: https://arxiv.org/abs/2312.05995
Code: https://github.com/javrtg/C2P
Abstract:
Estimating the relative camera pose from n ≥ 5 correspondences between two calibrated views is a fundamental task in computer vision. This process typically involves two stages: 1) estimating the essential matrix between the views, and 2) disambiguating among the four candidate relative poses that satisfy the epipolar geometry. In this paper, we demonstrate a novel approach that, for the first time, bypasses the second stage. Specifically, we show that it is possible to directly estimate the correct relative camera pose from correspondences without needing a post-processing step to enforce the cheirality constraint on the correspondences.
Building on recent advances in certifiable non-minimal optimization, we frame the relative pose estimation as a Quadratically Constrained Quadratic Program (QCQP). By applying the appropriate constraints, we ensure the estimation of a camera pose that corresponds to a valid 3D geometry and that is globally optimal when certified. We validate our method through exhaustive synthetic and real-world experiments, confirming the efficacy, efficiency and accuracy of the proposed approach.
0:00 Introduction
0:40 Pose from correspondences
1:36 Problem: Traditional approaches need disambiguation
2:58 Our approach
4:41 Summary
https://wn.com/Cvpr_2024_From_Correspondences_To_Pose_Non_Minimal_Relative_Pose_Without_Disambiguation
From Correspondences to Pose: Non-minimal Certifiably Optimal Relative Pose without Disambiguation
Authors: Javier Tirado-Garín and Javier Civera
Project Page: https://javrtg.github.io/C2P
Paper: https://arxiv.org/abs/2312.05995
Code: https://github.com/javrtg/C2P
Abstract:
Estimating the relative camera pose from n ≥ 5 correspondences between two calibrated views is a fundamental task in computer vision. This process typically involves two stages: 1) estimating the essential matrix between the views, and 2) disambiguating among the four candidate relative poses that satisfy the epipolar geometry. In this paper, we demonstrate a novel approach that, for the first time, bypasses the second stage. Specifically, we show that it is possible to directly estimate the correct relative camera pose from correspondences without needing a post-processing step to enforce the cheirality constraint on the correspondences.
Building on recent advances in certifiable non-minimal optimization, we frame the relative pose estimation as a Quadratically Constrained Quadratic Program (QCQP). By applying the appropriate constraints, we ensure the estimation of a camera pose that corresponds to a valid 3D geometry and that is globally optimal when certified. We validate our method through exhaustive synthetic and real-world experiments, confirming the efficacy, efficiency and accuracy of the proposed approach.
0:00 Introduction
0:40 Pose from correspondences
1:36 Problem: Traditional approaches need disambiguation
2:58 Our approach
4:41 Summary
- published: 05 Jun 2024
- views: 110