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# Deep Learning for Speech and Language

### Winter Seminar UPC TelecomBCN (January 24-31, 2017)

The aim of this course is to train students in methods of deep learning for speech and language. Recurrent Neural Networks (RNN) will be presented and analyzed in detail to understand the potential of these state of the art tools for time series processing. Engineering tips and scalability issues will be addressed to solve tasks such as machine translation, speech recognition, speech synthesis or question answering. Hands-on sessions will provide development skills so that attendees can become competent in contemporary data anlaytics tools.

## Course Instructors

| ![<NAME>][AntonioBonafonte-photo] | ![<NAME>][JoseAdrian-photo] | ![Marta R. Costa-jussà][MartaRuiz-photo] | ![<NAME>][JavierHernando-photo] | ![<NAME>][SantiagoPascual-photo] | ![<NAME>][ElisaSayrol-photo]  | ![<NAME>][XavierGiro-photo] |
|:-:|:-:|:-:|:-:|:-:|:-:|:-:|
| [<NAME> (AF)][AntonioBonafonte-web] | [<NAME> (JA)][JoseAdrian-web] | [Marta Ruiz Costa-jussà (MR)][MartaRuiz-web] | [<NAME> (JH)][JavierHernando-web] | [Santiago Pascual (SP)][SantiagoPascual-web] |  [<NAME> (ES)][ElisaSayrol-web]  | [<NAME>-i-Nieto (XG)][XavierGiro-web] |

[AntonioBonafonte-photo]: img/instructors/ToniBonafonte-160x160.jpg "AntonioBonafonte"
[JoseAdrian-photo]: img/instructors/JoseAdrian-160x160.jpg "<NAME>"
[MartaRuiz-photo]: img/instructors/MartaRuiz-160x160.jpg "<NAME>"
[JavierHernando-photo]: img/instructors/JavierHernando-120x120.jpg "<NAME>"
[SantiagoPascual-photo]: img/instructors/SantiPascual-160x160.jpg "<NAME>"
[ElisaSayrol-photo]: img/instructors/ElisaSayrol.jpg "<NAME>"
[XavierGiro-photo]: img/instructors/XavierGiro.jpg "<NAME>"

[AntonioBonafonte-web]: https://scholar.google.es/citations?user=C5AUXO4AAAAJ&hl=en&oi=ao
[JoseAdrian-web]: http://futur.upc.edu/JoseAdrianRodriguezFonollosa
[MartaRuiz-web]: http://futur.upc.edu/MartaRuizCostajussa
[JavierHernando-web]: https://scholar.google.es/citations?user=dTPbsfMAAAAJ&hl=en
[SantiagoPascual-web]: https://github.com/santi-pdp
[ElisaSayrol-web]: https://imatge.upc.edu/web/people/elisa-sayrol
[XavierGiro-web]: https://imatge.upc.edu/web/people/xavier-giro

## Invited talks
This 2017 edition of the seminar will include two invited talks

### [<NAME>](http://www.tid.es/research/researchers/joan-serra), from [Telefonica Research](http://www.tid.es/research).

Title: Facts and myths about deep learning.

Abstract: Deep learning has revolutionized the traditional machine learning pipeline, with impressive results in domains such as computer vision, speech analysis, or natural language processing. The concept has gone beyond research/application environments, and permeated into the mass media, news blogs, job offers, startup investors, or big company executives' meetings. But what is behind deep learning? Why has it become so mainstream? What can we expect from it? In this talk, I will highlight a number of facts and myths that will provide a shallow answer to the previous questions. While doing that, I will also highlight various applications we have worked on at our lab. Overall, the talk wants to place a series of basic concepts, while giving ground for reflection or discussion on the topic.


### [<NAME>](http://www.jordipons.me/) from the [Music Technology Group](http://www.mtg.upf.edu/) of the Universitat Pompeu Fabra (UPF)

Title: To be announced

Abstract: To be announced


## Organizers

| ![logo-etsetb] | ![logo-talp] | ![logo-gpi] | ![logo-upc] | 
|:------------:|:------------:|:------------:|:------------:|
| [UPC ETSETB TelecomBCN](etsetb-web) | [UPC TALP Group](talp-web) | [UPC Image Processing Group](gpi-web) | [Universitat Politecnica de Catalunya (UPC)](upc-web) |

[etsetb-web]: https://www.etsetb.upc.edu/en/
[talp-web]: http://www.talp.upc.edu/
[upc-web]: http://www.upc.edu/?set_language=en<commit_msg>Jordi Pons abstract and title added<commit_after>---
layout: page
title:
permalink: /
feature-img: "img/upc_heading.jpg"
hide: true
---

# Deep Learning for Speech and Language

### Winter Seminar UPC TelecomBCN (January 24-31, 2017)

The aim of this course is to train students in methods of deep learning for speech and language. Recurrent Neural Networks (RNN) will be presented and analyzed in detail to understand the potential of these state of the art tools for time series processing. Engineering tips and scalability issues will be addressed to solve tasks such as machine translation, speech recognition, speech synthesis or question answering. Hands-on sessions will provide development skills so that attendees can become competent in contemporary data anlaytics tools.

## Course Instructors

| ![<NAME>][AntonioBonafonte-photo] | ![<NAME>][JoseAdrian-photo] | ![Marta R. Costa-jussà][MartaRuiz-photo] | ![<NAME>][JavierHernando-photo] | ![Santiago Pascual][SantiagoPascual-photo] | ![<NAME>][ElisaSayrol-photo]  | ![<NAME>-Nieto][XavierGiro-photo] |
|:-:|:-:|:-:|:-:|:-:|:-:|:-:|
| [<NAME> (AF)][AntonioBonafonte-web] | [<NAME> (JA)][JoseAdrian-web] | [Marta Ruiz Costa-jussà (MR)][MartaRuiz-web] | [<NAME> (JH)][JavierHernando-web] | [Santiago Pascual (SP)][SantiagoPascual-web] |  [Elisa Sayrol (ES)][ElisaSayrol-web]  | [<NAME>-Nieto (XG)][XavierGiro-web] |

[AntonioBonafonte-photo]: img/instructors/ToniBonafonte-160x160.jpg "AntonioBonafonte"
[JoseAdrian-photo]: img/instructors/JoseAdrian-160x160.jpg "<NAME>"
[MartaRuiz-photo]: img/instructors/MartaRuiz-160x160.jpg "<NAME>"
[JavierHernando-photo]: img/instructors/JavierHernando-120x120.jpg "<NAME>"
[SantiagoPascual-photo]: img/instructors/SantiPascual-160x160.jpg "<NAME>"
[ElisaSayrol-photo]: img/instructors/ElisaSayrol.jpg "<NAME>"
[XavierGiro-photo]: img/instructors/XavierGiro.jpg "<NAME>"

[AntonioBonafonte-web]: https://scholar.google.es/citations?user=C5AUXO4AAAAJ&hl=en&oi=ao
[JoseAdrian-web]: http://futur.upc.edu/JoseAdrianRodriguezFonollosa
[MartaRuiz-web]: http://futur.upc.edu/MartaRuizCostajussa
[JavierHernando-web]: https://scholar.google.es/citations?user=dTPbsfMAAAAJ&hl=en
[SantiagoPascual-web]: https://github.com/santi-pdp
[ElisaSayrol-web]: https://imatge.upc.edu/web/people/elisa-sayrol
[XavierGiro-web]: https://imatge.upc.edu/web/people/xavier-giro

## Invited talks
This 2017 edition of the seminar will include two invited talks

### [<NAME>](http://www.tid.es/research/researchers/joan-serra), from [Telefonica Research](http://www.tid.es/research).

Title: Facts and myths about deep learning.

Abstract: Deep learning has revolutionized the traditional machine learning pipeline, with impressive results in domains such as computer vision, speech analysis, or natural language processing. The concept has gone beyond research/application environments, and permeated into the mass media, news blogs, job offers, startup investors, or big company executives' meetings. But what is behind deep learning? Why has it become so mainstream? What can we expect from it? In this talk, I will highlight a number of facts and myths that will provide a shallow answer to the previous questions. While doing that, I will also highlight various applications we have worked on at our lab. Overall, the talk wants to place a series of basic concepts, while giving ground for reflection or discussion on the topic.


### [<NAME>](http://www.jordipons.me/) from the [Music Technology Group](http://www.mtg.upf.edu/) of the Universitat Pompeu Fabra (UPF)

Title: Deep learning & music informatics research

Abstract: A brief review of the state-of-the-art in music informatics research and deep learning reveals that such models achieved competitive results for several tasks in a relatively short amount of time. Due to these promising results, some researchers declare that is the time for a paradigm shift: from hand-crafted features and shallow classifiers to deep processing models. In the past, introducing machine learning for global modeling (ie. classification) resulted in a significant state-of-the-art advance. And now, some researchers think that another advance could be done by using data-driven feature extractors based on deep learning instead of using hand-crafted features. However, deep learning for music informatics research is still in its early ages - current systems are based on solutions proposed for computer vision or speech. We will present our work describing how to adapt these technologies for the music case.


## Organizers

| ![logo-etsetb] | ![logo-talp] | ![logo-gpi] | ![logo-upc] | 
|:------------:|:------------:|:------------:|:------------:|
| [UPC ETSETB TelecomBCN](etsetb-web) | [UPC TALP Group](talp-web) | [UPC Image Processing Group](gpi-web) | [Universitat Politecnica de Catalunya (UPC)](upc-web) |

[etsetb-web]: https://www.etsetb.upc.edu/en/
[talp-web]: http://www.talp.upc.edu/
[upc-web]: http://www.upc.edu/?set_language=en
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