Separating stereo audio mixture having no phase difference by convex clustering and disjointness map

Atsushi Hiruma; Kohei Yatabe; Yasuhiro Oikawa

doi:10.1109/IWAENC.2018.8521350

Separating stereo audio mixture having no phase difference by convex clustering and disjointness map

Atsushi Hiruma, Kohei Yatabe, Yasuhiro Oikawa

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Citations (Scopus)

Abstract

In this paper, a method of constructing binary masks for stereo source separation is proposed. The proposed method consists of two main factors: (1) Disjointness map, and (2) convex directional clustering. The disjointness map quantifies the degree of mixing at each time-frequency bin based on instantaneous frequencies. This map enables to effectively utilize phase information which is usually omitted in stereo music separation. Then, the convex clustering utilizes flexible definitions of adjacency of the time-frequency bins for incorporating more information into directional clustering. Experimental results indicate that the proposed method can obtain a mask closer to the ideal one than the conventional directional clustering.

Original language	English
Title of host publication	16th International Workshop on Acoustic Signal Enhancement, IWAENC 2018 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	266-270
Number of pages	5
ISBN (Electronic)	9781538681510
DOIs	https://doi.org/10.1109/IWAENC.2018.8521350
Publication status	Published - 2018 Nov 2
Event	16th International Workshop on Acoustic Signal Enhancement, IWAENC 2018 - Tokyo, Japan Duration: 2018 Sept 17 → 2018 Sept 20

Other

Other	16th International Workshop on Acoustic Signal Enhancement, IWAENC 2018
Country/Territory	Japan
City	Tokyo
Period	18/9/17 → 18/9/20

Keywords

Convex clustering
Graph adjacency matrix
Phase
Time-frequency masking
Weighted undirected graph

ASJC Scopus subject areas

Signal Processing
Acoustics and Ultrasonics

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10.1109/IWAENC.2018.8521350

Cite this

Separating stereo audio mixture having no phase difference by convex clustering and disjointness map. / Hiruma, Atsushi; Yatabe, Kohei; Oikawa, Yasuhiro.
16th International Workshop on Acoustic Signal Enhancement, IWAENC 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. p. 266-270 8521350.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Hiruma, A, Yatabe, K & Oikawa, Y 2018, Separating stereo audio mixture having no phase difference by convex clustering and disjointness map. in 16th International Workshop on Acoustic Signal Enhancement, IWAENC 2018 - Proceedings., 8521350, Institute of Electrical and Electronics Engineers Inc., pp. 266-270, 16th International Workshop on Acoustic Signal Enhancement, IWAENC 2018, Tokyo, Japan, 18/9/17. https://doi.org/10.1109/IWAENC.2018.8521350

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abstract = "In this paper, a method of constructing binary masks for stereo source separation is proposed. The proposed method consists of two main factors: (1) Disjointness map, and (2) convex directional clustering. The disjointness map quantifies the degree of mixing at each time-frequency bin based on instantaneous frequencies. This map enables to effectively utilize phase information which is usually omitted in stereo music separation. Then, the convex clustering utilizes flexible definitions of adjacency of the time-frequency bins for incorporating more information into directional clustering. Experimental results indicate that the proposed method can obtain a mask closer to the ideal one than the conventional directional clustering.",

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AB - In this paper, a method of constructing binary masks for stereo source separation is proposed. The proposed method consists of two main factors: (1) Disjointness map, and (2) convex directional clustering. The disjointness map quantifies the degree of mixing at each time-frequency bin based on instantaneous frequencies. This map enables to effectively utilize phase information which is usually omitted in stereo music separation. Then, the convex clustering utilizes flexible definitions of adjacency of the time-frequency bins for incorporating more information into directional clustering. Experimental results indicate that the proposed method can obtain a mask closer to the ideal one than the conventional directional clustering.

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KW - Graph adjacency matrix

KW - Phase

KW - Time-frequency masking

KW - Weighted undirected graph

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Separating stereo audio mixture having no phase difference by convex clustering and disjointness map

Abstract

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Keywords

ASJC Scopus subject areas

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