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Jan Büthe

4 accepted papers

2024

NOLACE: Improving Low-Complexity Speech Codec Enhancement Through Adaptive Temporal Shaping

ICASSP 2024accepted

Speech codec enhancement methods are designed to remove distortions added by speech codecs. While classical methods are very low in complexity and add zero delay, their effectiveness is rather limited. Compared to that, DNN-based methods deliver higher quality but they are typically high in complexi…

Cited by 0SourceScholar
2024

Noise-Robust DSP-Assisted Neural Pitch Estimation With Very Low Complexity

ICASSP 2024accepted

Pitch estimation is an essential step of many speech processing algorithms, including speech coding, synthesis, and enhancement. Recently, pitch estimators based on deep neural networks (DNNs) have been outperforming well-established DSP-based techniques. Unfortunately, these new estimators can be i…

Cited by 0SourceScholar
2023

Framewise Wavegan: High Speed Adversarial Vocoder In Time Domain With Very Low Computational Complexity

ICASSP 2023accepted

GAN vocoders are currently one of the state-of-the-art methods for building high-quality neural waveform generative models. However, most of their architectures require dozens of billion floating-point operations per second (GFLOPS) to generate speech waveforms in samplewise manner. This makes GAN v…

Cited by 0SourceScholar
2023

Low-Bitrate Redundancy Coding of Speech Using A Rate-Distortion-Optimized Variational Autoencoder

ICASSP 2023accepted

Robustness to packet loss is one of the main ongoing challenges in real-time speech communication. Deep packet loss concealment (PLC) techniques have recently demonstrated improved quality compared to traditional PLC. Despite that, all PLC techniques hit fundamental limitations when too much acousti…

Cited by 0SourceScholar