Towards End-to-end Speech-to-text Abstractive Summarization - Raúl Monteiro (Priberam)

[Diogo Pernes]

Dear all,

Exceptionally, the next session of the Priberam Machine Learning Lunch Seminars will be next week (Tuesday, June 6). It is time to showcase the research we do at Priberam and so we are proud to invite Raúl Monteiro,  a Research Scientist at Priberam who recently completed his Master's degree in Engineering Physics at Instituto Superior Técnico. He will discuss his research on end-to-end approaches for abstraction text-to-speech summarization.

The event will occur at 1 PM in Instituto Superior Técnico (room PA2), and we will provide lunch bags for attendees. To learn more about the event and register (which is mandatory if you plan to attend), please follow the link below:

https://www.eventbrite.pt/e/towards-end-to-end-speech-to-text-abstractive-summarization-tickets-644308452927

We hope to see you all there!

Kind regards,

Diogo Pernes

Priberam Labs
http://labs.priberam.com/

Priberam is hiring!

If you are interested in working with us please consult the available positions at priberam.com/careers.

PRIBERAM SEMINARS

__________________________________________________

Priberam Machine Learning Lunch Seminar
Speaker: Raúl Monteiro (Priberam)
Venue: Instituto Superior Técnico (room PA2)

Date: Tuesday, June 6, 2023
Time: 1 PM 

Title:

Towards End-to-end Speech-to-text Abstractive Summarization

Abstract:

Speech-to-text summarization is a time-saving technique used to filter and keep pace with the daily influx of broadcast news uploaded online. The emergence of powerful deep learning-based language models, boasting impressive text generation capabilities, has directed research attention towards summarization systems capable of producing concise paraphrased versions of document content, commonly referred to as abstractive summaries. The application of end-to-end modelling for speech-to-text abstractive summarization shows promise by enabling the generation of rich latent representations that directly exploit non-verbal and acoustic information extracted from the audio source. Nevertheless, the unavailability of publicly accessible extensive corpora specific to the broadcast news domain, containing paired audio and summary data, poses a challenge for fully supervised approaches to end-to-end modeling. In this presentation, the speaker will discuss his work on a strategy that leverages external data through transfer learning from a pre-trained text-to-text abstractive summarizer.

Short Bio:

Raul Monteiro is an NLP researcher at Priberam Labs. He obtained a Master's degree (MSc) in Engineering Physics from Instituto Superior Técnico in 2023. He conducted his master's thesis in collaboration with Priberam, concentrating on the domain of Speech-to-text Summarization. His research interests primarily revolve around Deep Learning and Speech Processing, with particular focus on Speech Summarization and Spoken Named Entity Recognition.

More info: http://labs.priberam.com/Academia-Partnerships/Seminars.aspx

Eventbrite:

https://www.eventbrite.pt/e/towards-end-to-end-speech-to-text-abstractive-summarization-tickets-644308452927

[Diogo Pernes]

ERRATA: research on end-to-end approaches for abstraction text-to-speech abstractive speech-to-text summarization.

(My LLM writing assistant hallucinated and I didn't notice (😄). My apologies to all of you.)

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From: priberam_...@googlegroups.com <priberam_...@googlegroups.com> on behalf of Diogo Pernes <diogo....@priberam.pt>
Sent: Tuesday, May 30, 2023 10:02 PM
To: priberam_...@googlegroups.com; isr-...@isr.tecnico.ulisboa.pt; si...@omni.isr.ist.utl.pt
Subject: [Priberam ML Seminars] Towards End-to-end Speech-to-text Abstractive Summarization - Raúl Monteiro (Priberam)

 

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