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Dear colleague,
We are happy to announce an additional webinar in the Language
Technology webinar series organized by the HiTZ research center (Basque
Center for Language Technology, http://hitz.eus). Instead of the usual
afternoon hour, it will take place at 10:00am CET (June 24).
Next webinar:
Speaker: Mikel Artetxe (FAIR (Meta AI))
Title: Is scale all you need?
Date: Jun 24, 2022, 10:00 CET
Summary: The development of advanced spoken language technologies
based on automatic speech recognition (ASR) and text-to-speech synthesis
(TTS) has enabled computers to either learn how to listen or speak. Many
applications and services are now available but still support fewer than
100 languages. Nearly 7000 living languages that are spoken by 350
million people remain uncovered. This is because the construction is
commonly done based on machine learning trained in a supervised fashion
where a large amount of paired speech and corresponding transcription is
required. In this talk, we will introduce a semi-supervised learning
mechanism based on a machine speech chain framework. First, we describe
the primary machine speech chain architecture that learns not only to
listen or speak but also to listen while speaking. The framework enables
ASR and TTS to teach each other given unpaired data. After that, we
describe the use of machine speech chain for code-switching and
cross-lingual ASR and TTS of several languages, including low-resourced
ethnic languages. Finally, we describe the recent multimodal machine
chain that mimics overall human communication to listen while speaking
and visualizing. With the support of image captioning and production
models, the framework enables ASR and TTS to improve their performance
using an image-only dataset.
Summary: Every once in a while, a new language model with gazillion
parameters makes a big splash in Twitter, smashing the previous SOTA in
some benchmarks or showing some impressive emerging capabilities. While
some may argue that scaling will eventually solve NLP, others are
skeptical about the scientific value of this trend. In this talk, I will
argue that scaling is not just engineering, but also comes with exciting
research questions. I will present some of our recent work in the topic,
and discuss our efforts to make large language models more accessible
for the community.
Bio:Mikel Artetxe is a Research Scientist at FAIR (Meta AI). His
primary area of research is multilingual NLP. Mikel was one the pioneers
of unsupervised machine translation, and has done extensive work on
cross-lingual representation learning. More recently, he has also been
working on natural language generation, few-shot learning, and
large-scale language models. Prior to joining FAIR, Mikel did his PhD at
the IXA group at the University of the Basque Country, and interned at
DeepMind, FAIR and Google.
Check past and upcoming webinars at the following url:
http://www.hitz.eus/webinars If you are interested in participating,
please complete this registration form:
http://www.hitz.eus/webinar_izenematea
If you cannot attend this seminar, but you want to be informed of the
following HiTZ webinars, please complete this registration form instead:
http://www.hitz.eus/webinar_info
Best wishes,
HiTZ Zentroa
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