Group Delay Function from All-Pole Models for Musical Instrument Recognition
Tutkimustuotos › › vertaisarvioitu
Yksityiskohdat
| Alkuperäiskieli | Englanti |
|---|---|
| Otsikko | Sound, Music, and Motion, 10th International Symposium, CMMR 2013, Marseille, France, October 15-18, 2013. Revised Selected Papers |
| Toimittajat | Mitsuko Aramaki, Olivier Derrien, Richard Kronland-Martinet, Solvi Ystad |
| Kustantaja | Springer International Publishing |
| Sivut | 606-618 |
| Sivumäärä | 18 |
| ISBN (elektroninen) | 978-3-319-12976-1 |
| ISBN (painettu) | 978-3-319-12975-4 |
| DOI - pysyväislinkit | |
| Tila | Julkaistu - 2014 |
| OKM-julkaisutyyppi | A4 Artikkeli konferenssijulkaisussa |
| Tapahtuma | International Symposium on Computer Music Multidisciplinary Research - Kesto: 1 tammikuuta 1900 → … |
Conference
| Conference | International Symposium on Computer Music Multidisciplinary Research |
|---|---|
| Ajanjakso | 1/01/00 → … |
Tiivistelmä
In this work, the feature based on the group delay function from all-pole models (APGD) is proposed for pitched musical instrument recognition. Conventionally, the spectrum-related features take into account merely the magnitude information, whereas the phase is often overlooked due to the complications related to its interpretation. However, there is often additional information concealed in the phase, which could be beneficial for recognition. The APGD is an elegant approach to inferring phase information, which lacks of the issues related to interpreting the phase and does not require extensive parameter adjustment. Having shown applicability for speech-related problems, it is now explored in terms of instrument recognition. The evaluation is performed with various instrument sets and shows noteworthy absolute accuracy gains of up to 7% compared to the baseline mel-frequency cepstral coefficients (MFCCs) case. Combined with the MFCCs and with feature selection, APGD demonstrates superiority over the baseline with all the evaluated sets.