[Corpora-List] Webinar by Sakriani Sakti (Japan Advanced Institute of Science and Technology)

HiTZ zentroa webinars.hitz at ehu.eus
Thu Apr 28 13:47:41 CEST 2022


**** We apologize for the multiple copies of this email. In case you are already registered to the next webinar, you do not need to register again. ****

The last post concerning the upcoming HiTZ webinar included incorrect information about Dr. Sakti's bio and summary. This email contains the correct information.

Apologies for the mix up!

------------------------------------------------------------------------ Dear colleague,

We are happy to announce the next webinar in the Language Technology webinar series organized by the HiTZ research center (Basque Center for Language Technology, http://hitz.eus). This will be the final webinar for the 2021-2022 series. You can check the videos of previous webinars and the schedule for upcoming webinars here: http://www.hitz.eus/webinars

Next webinar:

* Speaker: *Sakriani Sakti* (Japan Advanced Institute of Science and

Technology)

* Title: Semi-supervised Learning for Low-resource Multilingual and

Multimodal Speech Processing with Machine Speech Chain

* Date: *May 5, 2022, 15:00 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.

* Bio: Sakriani Sakti is currently an associate professor at Japan

Advanced Institute of Science and Technology (JAIST) Japan, adjunct

associate professor at Nara Institute of Science and Technology

(NAIST) Japan, visiting research scientist at RIKEN Center for

Advanced Intelligent Project (RIKEN AIP) Japan, and adjunct

professor at the University of Indonesia. She received DAAD-Siemens

Program Asia 21st Century Award in 2000 to study in Communication

Technology, University of Ulm, Germany, and received her MSc degree

in 2002. During her thesis work, she worked with the Speech

Understanding Department, DaimlerChrysler Research Center, Ulm,

Germany. She then worked as a researcher at ATR Spoken Language

Communication (SLC) Laboratories Japan in 2003-2009, and NICT SLC

Groups Japan in 2006-2011, which established multilingual speech

recognition for speech-to-speech translation. While working with ATR

and NICT, Japan, she continued her study (2005-2008) with Dialog

Systems Group University of Ulm, Germany, and received her Ph.D.

degree in 2008. She was actively involved in international

collaboration activities such as Asian Pacific Telecommunity Project

(2003-2007) and various speech-to-speech translation research

projects, including A-STAR and U-STAR (2006-2011). In 2011-2017, she

was an assistant professor at the Augmented Human Communication

Laboratory, NAIST, Japan. She also served as a visiting scientific

researcher of INRIA Paris-Rocquencourt, France, in 2015-2016, under

JSPS Strategic Young Researcher Overseas Visits Program for

Accelerating Brain Circulation. In 2018–2021, she was a research

associate professor at NAIST and a research scientist at RIKEN,

Center for Advanced Intelligent Project AIP, Japan. Currently, she

is an associate professor at JAIST, adjunct associate professor at

NAIST, visiting research scientist at RIKEN AIP, and adjunct

professor at the University of Indonesia. She is a member of JNS,

SFN, ASJ, ISCA, IEICE, and IEEE. Furthermore, she is currently a

committee member of IEEE SLTC (2021-2023) and an associate editor of

the IEEE/ACM Transactions on Audio, Speech, and Language Processing

(2020-2023). She was a board member of Spoken Language Technologies

for Under-resourced languages (SLTU) and the general chair of

SLTU2016. She was also the general chair of the "Digital Revolution

for Under-resourced Languages (DigRevURL)" Workshop as the

Interspeech Special Session in 2017 and DigRevURL Asia in 2019. She

was also the organizing committee of the Zero Resource Speech

Challenge 2019 and 2020. She was also involved in creating joint

ELRA and ISCA Special Interest Group on Under-resourced Languages

(SIGUL) and served as SIGUL Board since 2018. Last year, in

collaboration with UNESCO and ELRA, she was also the organizing

committee of the International Conference of "Language Technologies

for All (LT4All): Enabling Linguistic Diversity and Multilingualism

Worldwide". Her research interests lie in deep learning & graphical

model framework, statistical pattern recognition, zero-resourced

speech technology, multilingual speech recognition and synthesis,

spoken language translation, social-affective dialog system, and

cognitive-communication.

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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