Low-Rate Farrow Structure with Discrete-Lowpass and Polynomial Support for Audio Resampling. Chinaev, A., Thüne, P., & Enzner, G. In 2018 26th European Signal Processing Conference (EUSIPCO), pages 475-479, Sep., 2018.
![Low-Rate Farrow Structure with Discrete-Lowpass and Polynomial Support for Audio Resampling [pdf]](https://bibbase.org/img/filetypes/pdf.svg "pdf")
Paper doi abstract bibtex
Paper doi abstract bibtex Arbitrary sampling rate conversion (ASRC) of audio signals currently receives a lot of new attention due to its potential for aligning autonomous recording clients in ad-hoc acoustic sensor networks. State-of-the-art for digital-to-digital ASRC has been outlined in terms of a two-stage architecture comprising a) synchronous lowpass interpolation by an integer factor and b) subsequent asynchronous polynomial interpolation. While this composite ASRC achieves high resampling accuracy, its mere disadvantage is the intermediate oversampling to high rate. In our paper we thus fuse the high-rate discrete-time lowpass interpolation with a polynomial Farrow filter into a monolithic FIR filter form. We then show that decimation of the output rate effectively yields a polyphase set of Farrow filters with quasi-fixed coefficients. Simulations with broadband multitone signals confirm that the proposed low-rate monolithic ASRC achieves the same performance as the conventional composite resampling in terms of signal-to-interpolation-noise ratio. The main practical benefit of quasi-fixed coefficients of the system stands out when resampling by a small factor is desired, i.e., when the input rate almost matches the output rate - a scenario to be encountered in acoustic sensor networks.
@InProceedings{8553469,
author = {A. Chinaev and P. Thüne and G. Enzner},
booktitle = {2018 26th European Signal Processing Conference (EUSIPCO)},
title = {Low-Rate Farrow Structure with Discrete-Lowpass and Polynomial Support for Audio Resampling},
year = {2018},
pages = {475-479},
abstract = {Arbitrary sampling rate conversion (ASRC) of audio signals currently receives a lot of new attention due to its potential for aligning autonomous recording clients in ad-hoc acoustic sensor networks. State-of-the-art for digital-to-digital ASRC has been outlined in terms of a two-stage architecture comprising a) synchronous lowpass interpolation by an integer factor and b) subsequent asynchronous polynomial interpolation. While this composite ASRC achieves high resampling accuracy, its mere disadvantage is the intermediate oversampling to high rate. In our paper we thus fuse the high-rate discrete-time lowpass interpolation with a polynomial Farrow filter into a monolithic FIR filter form. We then show that decimation of the output rate effectively yields a polyphase set of Farrow filters with quasi-fixed coefficients. Simulations with broadband multitone signals confirm that the proposed low-rate monolithic ASRC achieves the same performance as the conventional composite resampling in terms of signal-to-interpolation-noise ratio. The main practical benefit of quasi-fixed coefficients of the system stands out when resampling by a small factor is desired, i.e., when the input rate almost matches the output rate - a scenario to be encountered in acoustic sensor networks.},
keywords = {audio signal processing;FIR filters;interpolation;low-pass filters;polynomials;signal sampling;audio resampling;arbitrary sampling rate conversion;audio signals;ad-hoc acoustic sensor networks;digital-to-digital ASRC;two-stage architecture comprising;synchronous lowpass interpolation;integer factor;composite ASRC;high-rate discrete-time lowpass interpolation;polynomial Farrow filter;monolithic FIR filter form;quasifixed coefficients;broadband multitone signals;low-rate monolithic ASRC;signal-to-interpolation-noise ratio;low-rate Farrow structure;polynomial support;autonomous recording clients;composite resampling;subsequent asynchronous polynomial interpolation;Interpolation;Delays;Signal processing;Ad hoc networks;Acoustic sensors;Indexes;Switches;Asynchronous sampling rate conversion;sampling and interpolation;synchronization of ad-hoc acoustic sensor networks},
doi = {10.23919/EUSIPCO.2018.8553469},
issn = {2076-1465},
month = {Sep.},
url = {https://www.eurasip.org/proceedings/eusipco/eusipco2018/papers/1570438246.pdf},
}Downloads: 0
{"_id":"hdmj4YYquB7m3EdPj","bibbaseid":"chinaev-thne-enzner-lowratefarrowstructurewithdiscretelowpassandpolynomialsupportforaudioresampling-2018","authorIDs":[],"author_short":["Chinaev, A.","Thüne, P.","Enzner, G."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"firstnames":["A."],"propositions":[],"lastnames":["Chinaev"],"suffixes":[]},{"firstnames":["P."],"propositions":[],"lastnames":["Thüne"],"suffixes":[]},{"firstnames":["G."],"propositions":[],"lastnames":["Enzner"],"suffixes":[]}],"booktitle":"2018 26th European Signal Processing Conference (EUSIPCO)","title":"Low-Rate Farrow Structure with Discrete-Lowpass and Polynomial Support for Audio Resampling","year":"2018","pages":"475-479","abstract":"Arbitrary sampling rate conversion (ASRC) of audio signals currently receives a lot of new attention due to its potential for aligning autonomous recording clients in ad-hoc acoustic sensor networks. State-of-the-art for digital-to-digital ASRC has been outlined in terms of a two-stage architecture comprising a) synchronous lowpass interpolation by an integer factor and b) subsequent asynchronous polynomial interpolation. While this composite ASRC achieves high resampling accuracy, its mere disadvantage is the intermediate oversampling to high rate. In our paper we thus fuse the high-rate discrete-time lowpass interpolation with a polynomial Farrow filter into a monolithic FIR filter form. We then show that decimation of the output rate effectively yields a polyphase set of Farrow filters with quasi-fixed coefficients. Simulations with broadband multitone signals confirm that the proposed low-rate monolithic ASRC achieves the same performance as the conventional composite resampling in terms of signal-to-interpolation-noise ratio. The main practical benefit of quasi-fixed coefficients of the system stands out when resampling by a small factor is desired, i.e., when the input rate almost matches the output rate - a scenario to be encountered in acoustic sensor networks.","keywords":"audio signal processing;FIR filters;interpolation;low-pass filters;polynomials;signal sampling;audio resampling;arbitrary sampling rate conversion;audio signals;ad-hoc acoustic sensor networks;digital-to-digital ASRC;two-stage architecture comprising;synchronous lowpass interpolation;integer factor;composite ASRC;high-rate discrete-time lowpass interpolation;polynomial Farrow filter;monolithic FIR filter form;quasifixed coefficients;broadband multitone signals;low-rate monolithic ASRC;signal-to-interpolation-noise ratio;low-rate Farrow structure;polynomial support;autonomous recording clients;composite resampling;subsequent asynchronous polynomial interpolation;Interpolation;Delays;Signal processing;Ad hoc networks;Acoustic sensors;Indexes;Switches;Asynchronous sampling rate conversion;sampling and interpolation;synchronization of ad-hoc acoustic sensor networks","doi":"10.23919/EUSIPCO.2018.8553469","issn":"2076-1465","month":"Sep.","url":"https://www.eurasip.org/proceedings/eusipco/eusipco2018/papers/1570438246.pdf","bibtex":"@InProceedings{8553469,\n author = {A. Chinaev and P. Thüne and G. Enzner},\n booktitle = {2018 26th European Signal Processing Conference (EUSIPCO)},\n title = {Low-Rate Farrow Structure with Discrete-Lowpass and Polynomial Support for Audio Resampling},\n year = {2018},\n pages = {475-479},\n abstract = {Arbitrary sampling rate conversion (ASRC) of audio signals currently receives a lot of new attention due to its potential for aligning autonomous recording clients in ad-hoc acoustic sensor networks. State-of-the-art for digital-to-digital ASRC has been outlined in terms of a two-stage architecture comprising a) synchronous lowpass interpolation by an integer factor and b) subsequent asynchronous polynomial interpolation. While this composite ASRC achieves high resampling accuracy, its mere disadvantage is the intermediate oversampling to high rate. In our paper we thus fuse the high-rate discrete-time lowpass interpolation with a polynomial Farrow filter into a monolithic FIR filter form. We then show that decimation of the output rate effectively yields a polyphase set of Farrow filters with quasi-fixed coefficients. Simulations with broadband multitone signals confirm that the proposed low-rate monolithic ASRC achieves the same performance as the conventional composite resampling in terms of signal-to-interpolation-noise ratio. The main practical benefit of quasi-fixed coefficients of the system stands out when resampling by a small factor is desired, i.e., when the input rate almost matches the output rate - a scenario to be encountered in acoustic sensor networks.},\n keywords = {audio signal processing;FIR filters;interpolation;low-pass filters;polynomials;signal sampling;audio resampling;arbitrary sampling rate conversion;audio signals;ad-hoc acoustic sensor networks;digital-to-digital ASRC;two-stage architecture comprising;synchronous lowpass interpolation;integer factor;composite ASRC;high-rate discrete-time lowpass interpolation;polynomial Farrow filter;monolithic FIR filter form;quasifixed coefficients;broadband multitone signals;low-rate monolithic ASRC;signal-to-interpolation-noise ratio;low-rate Farrow structure;polynomial support;autonomous recording clients;composite resampling;subsequent asynchronous polynomial interpolation;Interpolation;Delays;Signal processing;Ad hoc networks;Acoustic sensors;Indexes;Switches;Asynchronous sampling rate conversion;sampling and interpolation;synchronization of ad-hoc acoustic sensor networks},\n doi = {10.23919/EUSIPCO.2018.8553469},\n issn = {2076-1465},\n month = {Sep.},\n url = {https://www.eurasip.org/proceedings/eusipco/eusipco2018/papers/1570438246.pdf},\n}\n\n","author_short":["Chinaev, A.","Thüne, P.","Enzner, G."],"key":"8553469","id":"8553469","bibbaseid":"chinaev-thne-enzner-lowratefarrowstructurewithdiscretelowpassandpolynomialsupportforaudioresampling-2018","role":"author","urls":{"Paper":"https://www.eurasip.org/proceedings/eusipco/eusipco2018/papers/1570438246.pdf"},"keyword":["audio signal processing;FIR filters;interpolation;low-pass filters;polynomials;signal sampling;audio resampling;arbitrary sampling rate conversion;audio signals;ad-hoc acoustic sensor networks;digital-to-digital ASRC;two-stage architecture comprising;synchronous lowpass interpolation;integer factor;composite ASRC;high-rate discrete-time lowpass interpolation;polynomial Farrow filter;monolithic FIR filter form;quasifixed coefficients;broadband multitone signals;low-rate monolithic ASRC;signal-to-interpolation-noise ratio;low-rate Farrow structure;polynomial support;autonomous recording clients;composite resampling;subsequent asynchronous polynomial interpolation;Interpolation;Delays;Signal processing;Ad hoc networks;Acoustic sensors;Indexes;Switches;Asynchronous sampling rate conversion;sampling and interpolation;synchronization of ad-hoc acoustic sensor networks"],"metadata":{"authorlinks":{}},"downloads":0},"bibtype":"inproceedings","biburl":"https://raw.githubusercontent.com/Roznn/EUSIPCO/main/eusipco2018url.bib","creationDate":"2021-02-13T15:38:40.453Z","downloads":0,"keywords":["audio signal processing;fir filters;interpolation;low-pass filters;polynomials;signal sampling;audio resampling;arbitrary sampling rate conversion;audio signals;ad-hoc acoustic sensor networks;digital-to-digital asrc;two-stage architecture comprising;synchronous lowpass interpolation;integer factor;composite asrc;high-rate discrete-time lowpass interpolation;polynomial farrow filter;monolithic fir filter form;quasifixed coefficients;broadband multitone signals;low-rate monolithic asrc;signal-to-interpolation-noise ratio;low-rate farrow structure;polynomial support;autonomous recording clients;composite resampling;subsequent asynchronous polynomial interpolation;interpolation;delays;signal processing;ad hoc networks;acoustic sensors;indexes;switches;asynchronous sampling rate conversion;sampling and interpolation;synchronization of ad-hoc acoustic sensor networks"],"search_terms":["low","rate","farrow","structure","discrete","lowpass","polynomial","support","audio","resampling","chinaev","thüne","enzner"],"title":"Low-Rate Farrow Structure with Discrete-Lowpass and Polynomial Support for Audio Resampling","year":2018,"dataSources":["yiZioZximP7hphDpY","iuBeKSmaES2fHcEE9"]}