The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Stereo Time-Scale Modification Using Sum and Difference Transformation
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In the citing paper
“A single channel is used in the proposed method as multi-channel TSM is rarely considered (Roberts and Paliwal, 2018).”
From An objective measure of quality for time-scale modification of audio (2021) · cites this paper as Roberts and Paliwal, 2018
In the citing paper
“All the processed sounds were loudness normalized according to ITU-BS.1770recommendation [31] to prevent loudness differences from affecting the grades.”
From Extreme Audio Time Stretching Using Neural Synthesis (2023) · cites this paper as [31]
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Citations
Cites
Improved phase vocoder time-scale modification of audio
Laroche, J., & Dolson, M. (1999) · IEEE Transactions on Speech and Audio Processing · doi:10.1109/89.759041 · Cited by 276
Improving Time-Scale Modification of Music Signals Using Harmonic-Percussive Separation
Driedger, J., Muller, M., & Ewert, S. (2014) · IEEE Signal Processing Letters · doi:10.1109/lsp.2013.2294023 · Cited by 64
Audio Time Stretching Using Fuzzy Classification of Spectral Bins
Damskägg, E.-P., & Välimäki, V. (2017) · Applied Sciences · doi:10.3390/app7121293 · Cited by 34
Research works printed but not linked: 12
- 10.1109/TASSP.1976.1162810 · DOI
- Ravelli, Fast implementation for nonlinear time-scaling of stereo signals, 182
- 10.1109/NCC.2017.8077073 · DOI · Paper page
- Rudresh, 2018, Epoch-synchronous overlap-add (esola) for time-and pitch-scale modification of speech signals
- Bonada, Automatic technique in frequency domain for near-lossless time-scale modification of audio
- Altoe, 2012, A transient-preserving audio time-stretching algorithm and a real-time realization for a commercial music product
- Blauert, 1997, Spatial hearing: the psychophysics of human sound localization
- Ryan, 2002, Communications and Information Systems
- Avendano, Frequency domain techniques for stereo to multichannel upmix, 1
- 10.1109/ICASSP.1993.319366 · DOI · Paper page
- Driedger, Tsm toolbox: Matlab implementations of time-scale modification algorithms, 1
- 10.1145/3133850.3133858 · DOI
Cited by
A time-scale modification dataset with subjective quality labels
Roberts, T., & Paliwal, K. K. (2020) · The Journal of the Acoustical Society of America · doi:10.1121/10.0001567 · Cited by 4
Self-citationAn objective measure of quality for time-scale modification of audio
Roberts, T., & Paliwal, K. K. (2021) · The Journal of the Acoustical Society of America · doi:10.1121/10.0003753 · Cited by 2
Self-citationExtreme Audio Time Stretching Using Neural Synthesis
Fierro, L., Wright, A., Välimäki, V., & Hämäläinen, M. (2023) · ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) · doi:10.1109/icassp49357.2023.10094738 · Cited by 2
Metadata
- Authors
- Roberts, T., & Paliwal, K. K.
- Venue
- 2018 12th International Conference on Signal Processing and Communication Systems (ICSPCS)
- Publisher
- IEEE
- Published
- 2018-12
- Pages
- 1-5
- Cited by
- 1
- References
- 3
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
