Multi-source localization by using offset residual weight
Abstract Multiple sound source localization is a hot issue of concern in recent years. The Single Source Zone (SSZ) based localization methods achieve good performance due to the detection and utilization of the Time-Frequency (T-F) zone where only one source is dominant. However, some T-F points co...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2021-06-01
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| Series: | EURASIP Journal on Audio, Speech, and Music Processing |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13636-021-00211-w |
| _version_ | 1819083594306420736 |
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| author | Maoshen Jia Shang Gao Changchun Bao |
| author_facet | Maoshen Jia Shang Gao Changchun Bao |
| author_sort | Maoshen Jia |
| collection | DOAJ |
| description | Abstract Multiple sound source localization is a hot issue of concern in recent years. The Single Source Zone (SSZ) based localization methods achieve good performance due to the detection and utilization of the Time-Frequency (T-F) zone where only one source is dominant. However, some T-F points consisting of components from multiple sources are also included in the detected SSZ sometimes. Once a T-F point in SSZ is contributed by multiple components, this point is defined as an outlier. The existence of outliers within the detected SSZ is usually an unavoidable problem for SSZ-based methods. To solve this problem, a multi-source localization by using offset residual weight is proposed in this paper. In this method, an assumption is developed: the direction estimated by all the T-F points within the detected SSZ has a difference along with the actual direction of sources. But this difference is much smaller than the difference between the directions estimated by the outliers along with the actual source localization. After verifying this assumption experimentally, Point Offset Residual Weight (PORW) and Source Offset Residual Weight (SORW) are proposed to reduce the influence of outliers on the localization results. Then, a composite weight is formed by combining PORW and SORW, which can effectively distinguish the outliers and desired points. After that, the outliers are removed by composite weight. Finally, a statistical histogram of DOA estimation with outliers removed is used for multi-source localization. The objective evaluation of the proposed method is conducted in various simulated environments. The results show that the proposed method achieves a better performance compared with the reference methods in sources localization. |
| first_indexed | 2024-12-21T20:35:03Z |
| format | Article |
| id | doaj.art-a3be92935d774223810b06c47c6c5ee9 |
| institution | Directory Open Access Journal |
| issn | 1687-4722 |
| language | English |
| last_indexed | 2024-12-21T20:35:03Z |
| publishDate | 2021-06-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Audio, Speech, and Music Processing |
| spelling | doaj.art-a3be92935d774223810b06c47c6c5ee92022-12-21T18:51:08ZengSpringerOpenEURASIP Journal on Audio, Speech, and Music Processing1687-47222021-06-012021111810.1186/s13636-021-00211-wMulti-source localization by using offset residual weightMaoshen Jia0Shang Gao1Changchun Bao2School of Information and Communication Engineering, Faculty of Information Technology, Beijing University of TechnologySchool of Information and Communication Engineering, Faculty of Information Technology, Beijing University of TechnologySchool of Information and Communication Engineering, Faculty of Information Technology, Beijing University of TechnologyAbstract Multiple sound source localization is a hot issue of concern in recent years. The Single Source Zone (SSZ) based localization methods achieve good performance due to the detection and utilization of the Time-Frequency (T-F) zone where only one source is dominant. However, some T-F points consisting of components from multiple sources are also included in the detected SSZ sometimes. Once a T-F point in SSZ is contributed by multiple components, this point is defined as an outlier. The existence of outliers within the detected SSZ is usually an unavoidable problem for SSZ-based methods. To solve this problem, a multi-source localization by using offset residual weight is proposed in this paper. In this method, an assumption is developed: the direction estimated by all the T-F points within the detected SSZ has a difference along with the actual direction of sources. But this difference is much smaller than the difference between the directions estimated by the outliers along with the actual source localization. After verifying this assumption experimentally, Point Offset Residual Weight (PORW) and Source Offset Residual Weight (SORW) are proposed to reduce the influence of outliers on the localization results. Then, a composite weight is formed by combining PORW and SORW, which can effectively distinguish the outliers and desired points. After that, the outliers are removed by composite weight. Finally, a statistical histogram of DOA estimation with outliers removed is used for multi-source localization. The objective evaluation of the proposed method is conducted in various simulated environments. The results show that the proposed method achieves a better performance compared with the reference methods in sources localization.https://doi.org/10.1186/s13636-021-00211-wMultiple sound sources localizationDirection of arrival estimationReverberationSoundfield microphone |
| spellingShingle | Maoshen Jia Shang Gao Changchun Bao Multi-source localization by using offset residual weight EURASIP Journal on Audio, Speech, and Music Processing Multiple sound sources localization Direction of arrival estimation Reverberation Soundfield microphone |
| title | Multi-source localization by using offset residual weight |
| title_full | Multi-source localization by using offset residual weight |
| title_fullStr | Multi-source localization by using offset residual weight |
| title_full_unstemmed | Multi-source localization by using offset residual weight |
| title_short | Multi-source localization by using offset residual weight |
| title_sort | multi source localization by using offset residual weight |
| topic | Multiple sound sources localization Direction of arrival estimation Reverberation Soundfield microphone |
| url | https://doi.org/10.1186/s13636-021-00211-w |
| work_keys_str_mv | AT maoshenjia multisourcelocalizationbyusingoffsetresidualweight AT shanggao multisourcelocalizationbyusingoffsetresidualweight AT changchunbao multisourcelocalizationbyusingoffsetresidualweight |