Search Results for author: Joachim köhler

Found 9 papers, 4 papers with code

Human and Automatic Speech Recognition Performance on German Oral History Interviews

no code implementations18 Jan 2022 Michael Gref, Nike Matthiesen, Christoph Schmidt, Sven Behnke, Joachim köhler

We investigate the influence of different adaptation data on robustness and generalization for clean and noisy oral history interviews.

Automatic Speech Recognition speech-recognition

Flexible Table Recognition and Semantic Interpretation System

1 code implementation25 May 2021 Marcin Namysl, Alexander M. Esser, Sven Behnke, Joachim köhler

Moreover, to incorporate the extraction of semantic information, we develop a graph-based table interpretation method.

Table Detection Table Extraction +1

NAT: Noise-Aware Training for Robust Neural Sequence Labeling

1 code implementation ACL 2020 Marcin Namysl, Sven Behnke, Joachim köhler

To this end, we formulate the noisy sequence labeling problem, where the input may undergo an unknown noising process and propose two Noise-Aware Training (NAT) objectives that improve robustness of sequence labeling performed on perturbed input: Our data augmentation method trains a neural model using a mixture of clean and noisy samples, whereas our stability training algorithm encourages the model to create a noise-invariant latent representation.

Data Augmentation named-entity-recognition +2

Two-Staged Acoustic Modeling Adaption for Robust Speech Recognition by the Example of German Oral History Interviews

no code implementations19 Aug 2019 Michael Gref, Christoph Schmidt, Sven Behnke, Joachim köhler

In automatic speech recognition, often little training data is available for specific challenging tasks, but training of state-of-the-art automatic speech recognition systems requires large amounts of annotated speech.

Automatic Speech Recognition Data Augmentation +3

Towards a Knowledge Graph based Speech Interface

no code implementations23 May 2017 Ashwini Jaya Kumar, Sören Auer, Christoph Schmidt, Joachim köhler

Applications which use human speech as an input require a speech interface with high recognition accuracy.

Knowledge Graphs Question Answering +2

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