STT4SG-350: A Speech Corpus for All Swiss German Dialect Regions

no code implementations • 30 May 2023 • Michel Plüss, Jan Deriu, Yanick Schraner, Claudio Paonessa, Julia Hartmann, Larissa Schmidt, Christian Scheller, Manuela Hürlimann, Tanja Samardžić, Manfred Vogel, Mark Cieliebak

We train an ASR model on the training set and achieve an average BLEU score of 74. 7 on the test set.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +5

2nd Swiss German Speech to Standard German Text Shared Task at SwissText 2022

1 code implementation • 17 Jan 2023 • Michel Plüss, Yanick Schraner, Christian Scheller, Manfred Vogel

We present the results and findings of the 2nd Swiss German speech to Standard German text shared task at SwissText 2022.

Sentence

Swiss German Speech to Text system evaluation

no code implementations • 1 Jul 2022 • Yanick Schraner, Christian Scheller, Michel Plüss, Manfred Vogel

We compare the four systems to our STT model, referred to as FHNW from hereon after, and provide details on how we trained our model.

SDS-200: A Swiss German Speech to Standard German Text Corpus

1 code implementation • LREC 2022 • Michel Plüss, Manuela Hürlimann, Marc Cuny, Alla Stöckli, Nikolaos Kapotis, Julia Hartmann, Malgorzata Anna Ulasik, Christian Scheller, Yanick Schraner, Amit Jain, Jan Deriu, Mark Cieliebak, Manfred Vogel

We present SDS-200, a corpus of Swiss German dialectal speech with Standard German text translations, annotated with dialect, age, and gender information of the speakers.

Speech Synthesis Translation

Distilling Reinforcement Learning Tricks for Video Games

1 code implementation • 1 Jul 2021 • Anssi Kanervisto, Christian Scheller, Yanick Schraner, Ville Hautamäki

Reinforcement learning (RL) research focuses on general solutions that can be applied across different domains.

Q-Learning reinforcement-learning +2

Towards robust and domain agnostic reinforcement learning competitions

no code implementations • 7 Jun 2021 • William Hebgen Guss, Stephanie Milani, Nicholay Topin, Brandon Houghton, Sharada Mohanty, Andrew Melnik, Augustin Harter, Benoit Buschmaas, Bjarne Jaster, Christoph Berganski, Dennis Heitkamp, Marko Henning, Helge Ritter, Chengjie WU, Xiaotian Hao, Yiming Lu, Hangyu Mao, Yihuan Mao, Chao Wang, Michal Opanowicz, Anssi Kanervisto, Yanick Schraner, Christian Scheller, Xiren Zhou, Lu Liu, Daichi Nishio, Toi Tsuneda, Karolis Ramanauskas, Gabija Juceviciute

Reinforcement learning competitions have formed the basis for standard research benchmarks, galvanized advances in the state-of-the-art, and shaped the direction of the field.

reinforcement-learning Reinforcement Learning +1

Flatland Competition 2020: MAPF and MARL for Efficient Train Coordination on a Grid World

no code implementations • 30 Mar 2021 • Florian Laurent, Manuel Schneider, Christian Scheller, Jeremy Watson, Jiaoyang Li, Zhe Chen, Yi Zheng, Shao-Hung Chan, Konstantin Makhnev, Oleg Svidchenko, Vladimir Egorov, Dmitry Ivanov, Aleksei Shpilman, Evgenija Spirovska, Oliver Tanevski, Aleksandar Nikov, Ramon Grunder, David Galevski, Jakov Mitrovski, Guillaume Sartoretti, Zhiyao Luo, Mehul Damani, Nilabha Bhattacharya, Shivam Agarwal, Adrian Egli, Erik Nygren, Sharada Mohanty

However, the coordination of hundreds of agents in a real-life setting like a railway network remains challenging and the Flatland environment used for the competition models these real-world properties in a simplified manner.

Multi-agent Reinforcement Learning Scheduling

Flatland-RL : Multi-Agent Reinforcement Learning on Trains

no code implementations • 10 Dec 2020 • Sharada Mohanty, Erik Nygren, Florian Laurent, Manuel Schneider, Christian Scheller, Nilabha Bhattacharya, Jeremy Watson, Adrian Egli, Christian Eichenberger, Christian Baumberger, Gereon Vienken, Irene Sturm, Guillaume Sartoretti, Giacomo Spigler

In order to probe the potential of Machine Learning (ML) research on Flatland, we (1) ran a first series of RL and IL experiments and (2) design and executed a public Benchmark at NeurIPS 2020 to engage a large community of researchers to work on this problem.

Imitation Learning Multi-agent Reinforcement Learning +4

Swiss Parliaments Corpus, an Automatically Aligned Swiss German Speech to Standard German Text Corpus

1 code implementation • 6 Oct 2020 • Michel Plüss, Lukas Neukom, Christian Scheller, Manfred Vogel

We present the Swiss Parliaments Corpus (SPC), an automatically aligned Swiss German speech to Standard German text corpus.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2

Action Space Shaping in Deep Reinforcement Learning

1 code implementation • 2 Apr 2020 • Anssi Kanervisto, Christian Scheller, Ville Hautamäki

In this work, we aim to gain insight on these action space modifications by conducting extensive experiments in video-game environments.

Deep Reinforcement Learning reinforcement-learning +1

Sample Efficient Reinforcement Learning through Learning from Demonstrations in Minecraft

3 code implementations • 12 Mar 2020 • Christian Scheller, Yanick Schraner, Manfred Vogel

Sample inefficiency of deep reinforcement learning methods is a major obstacle for their use in real-world applications.

Deep Reinforcement Learning Minecraft +2