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Determined BSS Based on Time-Frequency Masking and Its Application to Harmonic Vector Analysis
- Source :
- IEEE/ACM Transactions on Audio, Speech, and Language Processing. 29:1609-1625
- Publication Year :
- 2021
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2021.
-
Abstract
- This paper proposes harmonic vector analysis (HVA) based on a general algorithmic framework of audio blind source separation (BSS) that is also presented in this paper. BSS for a convolutive audio mixture is usually performed by multichannel linear filtering when the numbers of microphones and sources are equal (determined situation). This paper addresses such determined BSS based on batch processing. To estimate the demixing filters, effective modeling of the source signals is important. One successful example is independent vector analysis (IVA) that models the signals via co-occurrence among the frequency components in each source. To give more freedom to the source modeling, a general framework of determined BSS is presented in this paper. It is based on the plug-and-play scheme using a primal-dual splitting algorithm and enables us to model the source signals implicitly through a time-frequency mask. By using the proposed framework, determined BSS algorithms can be developed by designing masks that enhance the source signals. As an example of its application, we propose HVA by defining a time-frequency mask that enhances the harmonic structure of audio signals via sparsity of cepstrum. The experiments showed that HVA outperforms IVA and independent low-rank matrix analysis (ILRMA) for both speech and music signals. A MATLAB code is provided along with the paper for a reference ( https://doi.org/10.24433/CO.9507820.v1 ).
- Subjects :
- Signal Processing (eess.SP)
FOS: Computer and information sciences
Sound (cs.SD)
Audio signal
Acoustics and Ultrasonics
Computer science
Speech processing
Blind signal separation
Computer Science - Sound
Harmonic analysis
Computational Mathematics
Audio and Speech Processing (eess.AS)
Computer Science::Sound
Cepstrum
FOS: Electrical engineering, electronic engineering, information engineering
Computer Science (miscellaneous)
Harmonic
Spectrogram
Electrical Engineering and Systems Science - Signal Processing
Electrical and Electronic Engineering
Algorithm
Linear filter
Electrical Engineering and Systems Science - Audio and Speech Processing
Subjects
Details
- ISSN :
- 23299304 and 23299290
- Volume :
- 29
- Database :
- OpenAIRE
- Journal :
- IEEE/ACM Transactions on Audio, Speech, and Language Processing
- Accession number :
- edsair.doi.dedup.....1c264d45986aca4b8460a890250b376c