Search Results for author: René Peinl

Found 6 papers, 1 papers with code

ASR Bundestag: A Large-Scale political debate dataset in German

no code implementations12 Feb 2023 Johannes Wirth, René Peinl

We present ASR Bundestag, a dataset for automatic speech recognition in German, consisting of 610 hours of aligned audio-transcript pairs for supervised training as well as 1, 038 hours of unlabeled audio snippets for self-supervised learning, based on raw audio data and transcriptions from plenary sessions and committee meetings of the German parliament.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2

Automatic Speech Recognition in German: A Detailed Error Analysis

no code implementations IEEE International Conference on Omni-layer Intelligent Systems (COINS) 2022 Johannes Wirth, René Peinl

The amount of freely available systems for automatic speech recognition (ASR) based on neural networks is growing steadily, with equally increasingly reliable predictions.

 Ranked #1 on Automatic Speech Recognition (ASR) on VoxPopuli (using extra training data)

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

Neural Speech Synthesis in German

no code implementations 14th International Conference on Advances in Human-oriented and Personalized Mechanisms, Technologies, and Services 2021 Johannes Wirth, Pascal Puchtler, René Peinl

While many speech synthesis systems based on deep neural networks are thoroughly evaluated and released for free use in English, models for languages with far less active speakers like German are scarcely trained and most often not published for common use.

Speech Synthesis Text-To-Speech Synthesis

Sprachsynthese -- State-of-the-Art in englischer und deutscher Sprache

no code implementations11 Jun 2021 René Peinl

Reading text aloud is an important feature for modern computer applications.

Speech Synthesis

HUI-Audio-Corpus-German: A high quality TTS dataset

1 code implementation11 Jun 2021 Pascal Puchtler, Johannes Wirth, René Peinl

The increasing availability of audio data on the internet lead to a multitude of datasets for development and training of text to speech applications, based on neural networks.

Vocal Bursts Intensity Prediction

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