Blind bandwidth extension of speech based on LPCNet - Schmidt, Konstantin; Edler, Bernd (European Signal Processing Conference, 2021)
A blind bandwidth extension is presented which improves the perceived quality of 4 kHz speech by artificially extending the speech's frequency range to 8 kHz. Based on the source-filter model of the human speech production, the speech signal is decomposed into spectral envelope and excitation signal and each of them is extrapolated separately. With this decomposition, good perceptual quality can be achieved while keeping the computational complexity low. The focus of this work is in the generation of an excitation signal with and autoregressive model that calculates a distribution for each audio sample conditioned on previous samples. This is achieved with a deep neural network following the architecture of LPCNet [1]. A listening test shows that it significantly improves the perceived quality of bandlimited speech. The system has an algorithmic delay of 30 ms and can be applied in state-of-the-art speech and audio codecs.
CRIS-Team Scopus Importer:2021-01-22
Keywords: Artificial bandwidth expansion; Audio super resolution; Bandwidth extension; Speech enhancement; Speech super resolution

Deep neural network based guided speech bandwidth extension - Schmidt, Konstantin; Edler, Bernd (147th Audio Engineering Society International Convention 2019, 2019)
Up to today telephone speech is still limited to the range of 200 to 3400 Hz since the predominant codecs in public switched telephone networks are AMR-NB, G.711 and G.722 [1, 2, 3]. Blind bandwidth extension (blind BWE, BBWE) can improve the perceived quality as well as the intelligibility of coded speech without changing the transmission network or the speech codec. The BBWE used in this work is based on deep neural networks (DNNs) and has already shown good performance [4]. Although this BBWE enhances the speech without producing too many artifacts it sometimes fails to enhance prominent fricatives which can result in muffled speech. In order to better synthesize prominent fricatives the BBWE is extended by sending a single bit of side information - here referred to as guided BWE. This bit may be transmitted e.g. by watermarking so that no changes to the transmission network or the speech codec have to be done. Different DNN configurations (including convolutional (Conv.) layers as well as long short-term memory layers (LSTM)) making use of this bit have been evaluated. The BBWE has a low computational complexity and an algorithmic delay of 12 ms only and can be applied in state-of-the-art speech and audio codecs.
CRIS-Team Scopus Importer:2019-12-10

Intelligent Gap Filling in Perceptual Transform Coding of Audio - Disch, Sascha; Niedermeier, Andreas; Helmrich, Christian; Neukam, Christian; Schmidt, Konstantin; Geiger, Ralf; Lecomte, Jérémie; Ghido, Florin; Nagel, Frederik; Edler, Bernd (141th AES Convention, 2016)
Intelligent Gap Filling (IGF) denotes a semi-parametric coding technique within modern codecs like MPEG-H-3D-Audio or the 3gpp-EVS-codec. IGF can be applied to fill spectral holes introduced by the quantization process in the encoder due to low-bitrate constraints. Typically, if the limited bit budget does not allow for transparent coding, spectral holes emerge in the high-frequency (HF) region of the signal first and increasingly affect the entire upper spectral range for lowest bitrates. At the decoder side, such spectral holes are substituted via IGF using synthetic HF content generated out of low-frequency (LF) content, and post-processing controlled by additional parametric side information. This paper provides an overview of the principles and functionalities of IGF and presents listening test data assessing the perceptual quality of IGF coded audio material.<br