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SLT-Code: A new hackathon to promote language diversity in speech technology

Two-day hackathon will provide a hands-on approach to building speech-technology applications for underrepresented languages; registration deadline is Sept. 30.

By Staff writer
September 26, 2022
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Nowadays, speech technology permeates our everyday life. From smart-home devices to in-car navigation systems to chatting with friends on the other side of the planet, countless speech applications inform our worlds and enable us to do things that were unthinkable only a few years ago and that we now take for granted.

However, in thinking about how this technology has changed the lives of so many, it’s worth recalling the famous quote from science fiction writer William Gibson: “The future is already here — it’s just not very evenly distributed.”

Register for SLT-Code
This two-day speech technology hackathon will focus on language diversity, with the goal of developing a diverse community of speech technology practitioners and researchers.
Register by Sept. 30

While a native English speaker can enjoy a wide set of technologies with state-of-the-art performances, the same might not be true for a Balinese or a Gulf Arabic speaker. We want to help change that.

The Spoken Language Technology Workshop (SLT) is the biannual flagship event of the IEEE Speech and Language Processing Technical Committee. As such, SLT brings together researchers from both academia and industry to present their work and learn about state-of-the-art technologies in fields such as automatic speech recognition, text-to-speech, spoken dialogue systems, and speech-to-speech translation.

Next year’s event will be significant, as it will be the first time a speech technology conference takes place in the Middle East and in an Arabic-speaking nation. In celebration of these milestones, the theme of this year’s event is “Languages of the world”.

The Spoken Language Technology (SLT) workshop will be held in Doha, Qatar, in January 2023, the first time that a speech conference will occur in the Middle East.
The Spoken Language Technology (SLT) workshop will be held in Doha, Qatar, in January 2023, the first time that a speech conference will occur in the Middle East.

Moreover, for the first time in the history of SLT, we are organizing SLT-Code, a two-day speech technology hackathon. Following the main workshop’s theme, the hackathon will focus on language diversity. Our goal: develop a diverse community of speech-technology practitioners and researchers, specifically targeting the inclusion of researchers from underrepresented regions and low-resource languages.

This year's areas of interest for the hackathon include (but are not limited to)

  • Low-resource languages, e.g., African, Indian, or Asian languages
  • Language identification
  • Automatic speech recognition
  • Machine translation
  • Text to speech 
  • Speech-to-speech translation

While participants will be free to use any technology of their preference, the organizers will support the following frameworks:

  • Lex/Alexa
  • Huggingface
  • Speechbrain
  • ESPNet
  • K2/Kaldi

We are looking forward to welcoming participants from different backgrounds and are eager to read about your speech technology ideas. To participate, please register by September 30, 2022.

Important dates

  • September 30, 2022: Call for applications and submission of idea proposals
  • October 12, 2022: Idea selection and invitation to participate
  • October 12 – November 1, 2022: Team-forming phase, mentor assignment
  • January 7 – 8, 2023: SLT-Code

Organizers

Thomas Schaaf (3M | M*Modal)
Gianni Di Caro (Carnegie Mellon University Qatar)
Shinji Watanabe (ESPNET | Carnegie Mellon University)
Paola Garcia (KALDI/K2 | Johns Hopkins University)
Mirco Ravanelli (SpeechBrain | Université de Montréal)
Alessandra Cervone (Amazon Alexa AI)
Mus'ab Husaini (QCRI)
Harshita Diddee (Microsoft)

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Economist, Prime Science
US, WA, Seattle
Amazon Prime is looking for an ambitious Economist to help create econometric insights for world-wide Prime. Prime is Amazon's premiere membership program, with over 200M members world-wide. This role is at the center of many major company decisions that impact Amazon's customers. These decisions span a variety of industries, each reflecting the diversity of Prime benefits. These range from fast-free e-commerce shipping, digital content (e.g., exclusive streaming video, music, gaming, photos), and grocery offerings. Prime Science creates insights that power these decisions. As an economist in this role, you will create statistical tools that embed causal interpretations. You will utilize massive data, state-of-the-art scientific computing, econometrics (causal, counterfactual/structural, time-series forecasting, experimentation), and machine-learning, to do so. Some of the science you create will be publishable in internal or external scientific journals and conferences. You will work closely with a team of economists, applied scientists, data professionals (business analysts, business intelligence engineers), product managers, and software engineers. You will create insights from descriptive statistics, as well as from novel statistical and econometric models. You will create internal-to-Amazon-facing automated scientific data products to power company decisions. You will write strategic documents explaining how senior company leaders should utilize these insights to create sustainable value for customers. These leaders will often include the senior-most leaders at Amazon. The team is unique in its exposure to company-wide strategies as well as senior leadership. It operates at the cutting-edge of utilizing data, econometrics, artificial intelligence, and machine-learning to form business strategies. A successful candidate will have demonstrated a capacity for building, estimating, and defending statistical models (e.g., causal, counterfactual, time-series, machine-learning) using software such as R, Python, or STATA. They will have a willingness to learn and apply a broad set of statistical and computational techniques to supplement deep-training in one area of econometrics. For example, many applications on the team use structural econometrics, machine-learning, and time-series forecasting. They rely on building scalable production software, which involves a broad set of world-class software-building skills often learned on-the-job. As a consequence, already-obtained knowledge of SQL, machine learning, and large-scale scientific computing using distributed computing infrastructures such as Spark-Scala or PySpark would be a plus. Additionally, this candidate will show a track-record of delivering projects well and on-time, preferably in collaboration with other team members (e.g. co-authors). Candidates must have very strong writing and emotional intelligence skills (for collaborative teamwork, often with colleagues in different functional roles), a growth mindset, and a capacity for dealing with a high-level of ambiguity. Endowed with these traits and on-the-job-growth, the role will provide the opportunity to have a large strategic, world-wide impact on the customer experiences of Prime members.
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