The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Temporal modulations in speech and music
Open accessAbstract
Speech and music have structured rhythms. Here we discuss a major acoustic correlate of spoken and musical rhythms, the slow (0.25-32Hz) temporal modulations in sound intensity and compare the modulation properties of speech and music. We analyze these modulations using over 25h of speech and over 39h of recordings of Western music. We show that the speech modulation spectrum is highly consistent across 9 languages (including languages with typologically different rhythmic characteristics). A different, but similarly consistent modulation spectrum is observed for music, including classical music played by single instruments of different types, symphonic, jazz, and rock. The temporal modulations of speech and music show broad but well-separated peaks around 5 and 2Hz, respectively. These acoustically dominant time scales may be intrinsic features of speech and music, a possibility which should be investigated using more culturally diverse samples in each domain. Distinct modulation timescales for speech and music could facilitate their perceptual analysis and its neural processing.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
SWITCHBOARD: telephone speech corpus for research and development
Godfrey, J. J., Holliman, E. C., & McDaniel, J. (1992) · [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing · doi:10.1109/icassp.1992.225858 · Cited by 2,134
Cortical tracking of hierarchical linguistic structures in connected speech
Ding, N., Melloni, L., Zhang, H., Tian, X., & Poeppel, D. (2016) · Nature Neuroscience · doi:10.1038/nn.4186 · Cited by 1,059
Self-citationMechanisms underlying selective neuronal tracking of attended speech at a “cocktail party”
Zion Golumbic, E. M., Ding, N., Bickel, S., Lakatos, P., Schevon, C. A., McKhann, G. M., Goodman, R. R., Emerson, R., Mehta, A. D., Simon, J. Z., et al. (2013) · Neuron · doi:10.1016/j.neuron.2012.12.037 · Cited by 909
Self-citation
Cited by
A New Unifying Account of the Roles of Neuronal Entrainment
Lakatos, P., Gross, J., & Thut, G. (2019) · Current Biology · doi:10.1016/j.cub.2019.07.075 · Cited by 508
Keitel, A., Gross, J., & Kayser, C. (2018) · PLOS Biology · doi:10.1371/journal.pbio.2004473 · Cited by 312
Distinct sensitivity to spectrotemporal modulation supports brain asymmetry for speech and melody
Albouy, P., Benjamin, L., Morillon, B., & Zatorre, R. J. (2020) · Science · doi:10.1126/science.aaz3468 · Cited by 298
Assaneo, M. F., & Poeppel, D. (2018) · Science Advances · doi:10.1126/sciadv.aao3842 · Cited by 164
Self-citationBiological principles for music and mental health
Bowling, D. L. (2023) · Translational Psychiatry · doi:10.1038/s41398-023-02671-4 · Cited by 64
Metadata
- Authors
- Ding, N., Patel, A. D., Chen, L., Butler, H., Luo, C., & Poeppel, D.
- Venue
- Neuroscience & Biobehavioral Reviews
- Publisher
- Elsevier BV
- Published
- 2017-10
- Volume
- 81
- Issue
- Pt B
- Pages
- 181-187
- ISSN
- 0149-7634 (ISSN-L)
- OpenAlex
- W2588767398
- Cited by
- 502
- References
- 3
- FWCI
- 19.33
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Temporal modulations in speech and music. https://app.cochat.ai/papers/10.1016/j.neubiorev.2017.02.011
- The paper
- Ding, N., Patel, A. D., Chen, L., Butler, H., Luo, C., & Poeppel, D. (2017). Temporal modulations in speech and music. Neuroscience & Biobehavioral Reviews. https://doi.org/10.1016/j.neubiorev.2017.02.011
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.