18 citations · 29 across the 12 of their papers we have counts for
12 papers
Parametric Object Coding in IVAS: Efficient Coding of Multiple Audio Objects at Low Bit Rates
Andrea Eichenseer, Srikanth Korse, Guillaume Fuchs +1
The recently standardized 3GPP codec for Immersive Voice and Audio Services (IVAS) includes a parametric mode for efficiently coding multiple audio objects at low bit rates. In thi…
Benchmarking Neural Speech Codec Intelligibility with SITool
Anna Leschanowsky, Kishor Kayyar Lakshminarayana, Anjana Rajasekhar +4
Speech intelligibility assessment is essential for evaluating neural speech codecs, yet most evaluation efforts focus on overall quality rather than intelligibility. Only a few pub…
UBGAN: Enhancing Coded Speech with Blind and Guided Bandwidth Extension
Kishan Gupta, Srikanth Korse, Andreas Brendel +2
In practical application of speech codecs, a multitude of factors such as the quality of the radio connection, limiting hardware or required user experience necessitate trade-offs…
A first-order DirAC-based parametric Ambisonic coder for immersive communications
Guillaume Fuchs, Florin Ghido, Dominik Weckbecker +1
Directional Audio Coding (DirAC) is a proven method for parametrically representing a 3D audio scene in B-format and is capable of reproducing it on arbitrary loudspeaker layouts.…
On Improving Error Resilience of Neural End-to-End Speech Coders
Kishan Gupta, Nicola Pia, Srikanth Korse +3
Error resilient tools like Packet Loss Concealment (PLC) and Forward Error Correction (FEC) are essential to maintain a reliable speech communication for applications like Voice ov…
Neural Speech Coding for Real-time Communications using Constant Bitrate Scalar Quantization
Andreas Brendel, Nicola Pia, Kishan Gupta +3
Neural audio coding has emerged as a vivid research direction by promising good audio quality at very low bitrates unachievable by classical coding techniques. Here, end-to-end tra…
NESC: Robust Neural End-2-End Speech Coding with GANs
Nicola Pia, Kishan Gupta, Srikanth Korse +2
Neural networks have proven to be a formidable tool to tackle the problem of speech coding at very low bit rates. However, the design of a neural coder that can be operated robustl…
PostGAN: A GAN-Based Post-Processor to Enhance the Quality of Coded Speech
Srikanth Korse, Nicola Pia, Kishan Gupta +1
The quality of speech coded by transform coding is affected by various artefacts especially when bitrates to quantize the frequency components become too low. In order to mitigate…
A DNN Based Post-Filter to Enhance the Quality of Coded Speech in MDCT Domain
Kishan Gupta, Srikanth Korse, Bernd Edler +1
Frequency domain processing, and in particular the use of Modified Discrete Cosine Transform (MDCT), is the most widespread approach to audio coding. However, at low bitrates, audi…
A Streamwise GAN Vocoder for Wideband Speech Coding at Very Low Bit Rate
Ahmed Mustafa, Jan Büthe, Srikanth Korse +3
Recently, GAN vocoders have seen rapid progress in speech synthesis, starting to outperform autoregressive models in perceptual quality with much higher generation speed. However,…
StyleMelGAN: An Efficient High-Fidelity Adversarial Vocoder with Temporal Adaptive Normalization
Ahmed Mustafa, Nicola Pia, Guillaume Fuchs
In recent years, neural vocoders have surpassed classical speech generation approaches in naturalness and perceptual quality of the synthesized speech. Computationally heavy models…
Enhancement Of Coded Speech Using a Mask-Based Post-Filter
Srikanth Korse, Kishan Gupta, Guillaume Fuchs
The quality of speech codecs deteriorates at low bitrates due to high quantization noise. A post-filter is generally employed to enhance the quality of the coded speech. In this pa…