127 - Masakhane and Participatory Research for African Languages, with Tosin Adewumi and Perez Ogayo

127 - Masakhane and Participatory Research for African Languages, with Tosin Adewumi and Perez Ogayo

Author: Allen Institute for Artificial Intelligence June 9, 2021 Duration: 47:17
We invited members of Masakhane, Tosin Adewumi and Perez Ogayo, to talk about their EMNLP Findings paper that discusses why typical research is limited for low-resourced NLP and how participatory research can help.   As a result of participatory research, Masakhane has many, many success stories: first datasets and benchmarks in African languages, first research on human evaluation specifically for MT for low-resource languages, etc. In this episode, we talked about one of them—MasakhaNER—in more detail. The hosts for this episode are Pradeep Dasigi and Ana Marasović. -------------------------- Tosin Adewumi is a PhD student at the Luleå University of Technology in Sweden. His Twitter handle: @tosintwit Perez Ogayo is an undergrad student at the African Leadership University in Rwanda. Her Twitter handle: @a_ogayo Masakhane is a grassroots organization whose mission is to strengthen and spur NLP research in African languages, for Africans, by Africans: https://www.masakhane.io/ Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages (Findings of EMNLP 2020): https://arxiv.org/abs/2010.02353 MasakhaNER: Named Entity Recognition for African languages (AfricaNLP Workshop @ EACL 2021): https://arxiv.org/abs/2103.11811

While NLP Highlights is currently on hiatus, its archive remains a compelling snapshot of conversations from the front lines of computational linguistics. Produced by the Allen Institute for Artificial Intelligence, this science podcast carved out a space for deep, researcher-led discussions about natural language processing. Each episode functions as an informal seminar, where the people actively designing algorithms and pushing the field forward explain their work in their own words. You'll hear about the nuanced challenges behind making machines understand, generate, and reason with human language, from foundational theories to unexpected applications. The dialogue in this podcast often delves into the "why" behind the research, not just the results, offering clarity on complex topics like machine translation, sentiment analysis, or large language models. It’s a chance to listen as experts articulate their thought processes, debates, and moments of insight, with all the candidness that comes from a conversation between peers. The views shared are personal perspectives from the hosts and their guests, independent of their affiliated institutions. For anyone curious about how machines learn to parse meaning, the archived episodes of NLP Highlights provide a thoughtful and accessible entry point.
Author: Language: English Episodes: 50

NLP Highlights
Podcast Episodes
103 - Processing Language in Social Media, with Brendan O'Connor [not-audio_url] [/not-audio_url]

Duration: 43:12
We talked to Brendan O’Connor for this episode about processing language in social media. Brendan started off by telling us about his projects that studied the linguistic and geographical patterns of African American Eng…
101 - The lottery ticket hypothesis, with Jonathan Frankle [not-audio_url] [/not-audio_url]

Duration: 41:16
In this episode, Jonathan Frankle describes the lottery ticket hypothesis, a popular explanation of how over-parameterization helps in training neural networks. We discuss pruning methods used to uncover subnetworks (win…
100 - NLP Startups, with Oren Etzioni [not-audio_url] [/not-audio_url]

Duration: 30:55
For our 100th episode, we invite AI2 CEO Oren Etzioni to talk to us about NLP startups. Oren has founded several successful startups, is himself an investor in startups, and helps with AI2's startup incubator. Some of ou…
98 - Analyzing Information Flow In Transformers, With Elena Voita [not-audio_url] [/not-audio_url]

Duration: 37:05
What function do the different attention heads serve in multi-headed attention models? In this episode, Lena describes how to use attribution methods to assess the importance and contribution of different heads in severa…
95 - Common sense reasoning, with Yejin Choi [not-audio_url] [/not-audio_url]

Duration: 35:29
In this episode, we invite Yejin Choi to talk about common sense knowledge and reasoning, a growing area in NLP. We start by discussing a working definition of “common sense” and the practical utility of studying it. We…