A time-warped MDCT approach to speech transform coding - Edler, Bernd; Disch, Sascha; Bayer, Stefan; Fuchs, Guillaume; Geiger, Ralf (126th AES Convention, 2009)
The modified discrete cosine transform (MDCT) is often used for audio coding due to its critical sampling property and good energy compaction, especially for harmonic tones with constant fundamental frequencies (pitch). However, in voiced human speech the pitch is time-varying and thus the energy is spread over several transform coefficients, leading to a reduction of coding efficiency. The approach presented herein compensates for pitch variation in each MDCT block by application of time-variant re-sampling. A dedicated signal adaptive transform window computation ensures the preservation of the time domain aliasing cancelation (TDAC) property. Re-sampling can be designed such that the duration of the processed blocks is not altered, facilitating the replacement of the conventional MDCT in existing audio coders.
UnivIS-Import:2019-03-25:Pub.2009.tech.IE.aulab.zentr.atimew

Improved arithmetic coding for Time-Warped MDCT based audio coding - Bayer, Stefan; Edler, Bernd (Proceedings of the IEEE 2013 Int. Conference on Acoustics, Speech and Signal Processing (ICASSP), 2013)
The Time-Warped Modified Discrete Cosine Transform (TW-MDCT) improves the energy compaction for harmonic signals with varying fundamental frequency compared to the plain MDCT. Adaptive context based entropy coding has the potential to provide higher gain over memoryless entropy coding. But in combination with the TW-MDCT, the context based adaptive coding may lead to suboptimal coding. This paper presents an algorithm for improving the context for the TW-MDCT. This is mainly achieved by exploiting already available information on the frequency variation needed by the TW-MDCT. This results in an improved entropy coding.<br
Keywords: Context; Harmonic analysis; Time-frequency analysis; Audio coding; Bit rate; Speech; Audio Coding; Entropy Coding; TW-MDCT; Arithmetic Coding

Low-Complexity Semi-Parametric Joint-Stereo Audio Transform Coding - Helmrich, Christian; Niedermeier, Andreas; Bayer, Stefan; Edler, Bernd (Proceedings, 23rd European Signal Processing Conference (EUSIPCO 2015), 2015)
Traditional audio codecs based on real-valued transforms utilize separate and largely independent algorithmic schemes for parametric coding of noise-like or high-frequency spectral components as well as channel pairs. It is shown that in the frequency-domain part of coders such as Extended HE-AAC, these schemes can be unified into a single algorithmic block located at the core of the modified discrete cosine transform path, enabling greater flexibility like semi-parametric coding and large savings in codec delay and complexity. This paper focuses on the stereo coding aspect of this block and demonstrates that, by using specially chosen spectral configurations when deriving the parametric side-information in the encoder, perceptual artifacts can be reduced and the spatial processing in the decoder can remain real-valued. Listening tests confirm the benefit of our proposal at intermediate bit-rates.<br

Refining Fundamental Frequency Estimates using Time Warping - Stöter, Fabian-Robert; Werner, Nils; Bayer, Stefan; Edler, Bernd (Proceedings of 23rd European Signal Processing Conference (EUSIPCO) 2015, 2015)
Algorithms for estimating the fundamental frequency (F0) of a signal vary in stability and accuracy. We propose a method which iteratively improves the estimates of such algorithms by applying in each step a time warp on the input signal based on the previously estimated fundamental frequency. This time warp is designed to lead to a nearly constant F0. A refine ment is then calculated through inverse time warping of the result of an F0 estimation applied to the warped signal. The proposed refinement algorithm is not limited to specific esti mators or optimized for specific input signal characteristics. The method is evaluated on synthetic audio signals as well as speech recordings and polyphonic music recordings. Results indicate a significant improvement on accuracy when using the proposed refinement in combination with several well-known F0 estimators.<br

Unison Source Separation - Stöter, Fabian-Robert; Bayer, Stefan; Edler, Bernd (17th International Conference on Digital Audio Effects (DAFx-14), 2014)
In this work we present a new scenario of analyzing and separating linear mixtures of musical instrument signals. When instruments are playing in unison, traditional source separation methods are not performing well. Although the sources share the same pitch, they often still differ in their modulation frequency caused by vibrato and/or tremolo effects. In this paper we propose source separation schemes that exploit AM/FM characteristics to improve the sep- aration quality of such mixtures. We show a method to process mixtures based on differences in their amplitude modulation fre- quency of the sources by using non-negative tensor factorization. Further, we propose an informed warped time domain approach for separating mixtures based on variations in the instantaneous frequencies of the sources.