5 papers
FFASR: Benchmarking Far-Field Automatic Speech Recognition using High-Fidelity Simulated RIRs
Shivam Saini, Eric Bezzam, Georg Götz +5
Far-field automatic speech recognition(ASR) degrades under reverberation, noise, and talker motion, yet the benchmarks that drive model selection emphasize close-microphone speech.…
Training DeepFilterNet with Accurate Room Acoustic Simulations Improves Single-Channel Speech Enhancement
Alessia Milo, Georg Götz, Steinar Guðjónsson +3
We investigate how the realism of synthetic room impulse response (RIR) datasets affects the training of DeepFilterNet3 for single-channel speech enhancement. We compare a DNS4 ima…
Improving multichannel speech enhancement through accurate room-acoustic simulations
Georg Götz, Alessia Milo, Steinar Guðjónsson +3
Room-acoustic simulations are widely used to augment training data for deep-learning-based speech enhancement. While most pipelines rely on simplified geometrical acoustics, wave-b…
Treble10: A high-quality dataset for far-field speech recognition, dereverberation, and enhancement
Sarabeth S. Mullins, Georg Götz, Eric Bezzam +2
Accurate far-field speech datasets are critical for tasks such as automatic speech recognition (ASR), dereverberation, speech enhancement, and source separation. However, current d…
Generative Data Augmentation Challenge: Synthesis of Room Acoustics for Speaker Distance Estimation
Jackie Lin, Georg Götz, Hermes Sampedro Llopis +9
This paper describes the synthesis of the room acoustics challenge as a part of the generative data augmentation workshop at ICASSP 2025. The challenge defines a unique generative…