Coherence-Based Frequency Subset Selection for Binaural RTF-vector-based Direction of Arrival Estimation for Multiple Speakers

Fejgin, Daniel; Doclo, Simon

doi:10.1109/iwaenc53105.2022.9914768

Cited by 6 publications

(13 citation statements)

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“…In this section, we review the RTF-vector-based DOA estimation method proposed in [8] that is based on finding the directions corresponding to the peaks of the spatial spectrum called frequency-averaged Hermitian angle spectrum.…”

Section: Rtf-vector-based Doa Estimationmentioning

confidence: 99%

“…the estimated head-mounted RTF vector ĝH d (k,l) is a good estimate for the direct-path RTF vector in (5) (of one of the speakers), the narrowband spatial spectrum ( 8) is integrated over a set K(l) of selected frequency bins, where it is likely that one speaker dominates over all other speakers, noise, and reverberation [8], i.e.,…”

Section: Rtf-vector-based Doa Estimationmentioning

confidence: 99%

“…In the context of DOA estimation, coherence-based quantities such as the coherent-to-diffuse ratio (CDR) are a common criterion for frequency subset selection [8,[14][15][16][17]. The usage of the CDR as a criterion for frequency subset selection can be motivated by the fact, that for higher values of the CDR at the respective TF bin it is more likely that a speaker dominates over all other speakers, noise, and reverberation at the respective TF bin.…”

Section: Rtf-vector-based Doa Estimationmentioning

confidence: 99%

“…Large research effort has already been dedicated to DOA estimation [10][11][12][13][14], in particular also for binaural hearing aid applications [7][8][9][15][16][17]. In [7] we proposed a DOA estimation method for a binaural hearing aid setup, which exploits an external microphone at an unknown position.…”

Section: Introductionmentioning

confidence: 99%

“…However, the methods in [3][4][5][6] considered only a single speaker. To address DOA estimation for multiple speakers, we introduced the so-called frequency-averaged Hermitian angle spectrum from which the DOAs were estimated as the directions corresponding to the peaks of this spatial spectrum (throughout the paper, we refer to a direction-dependent similarity score as a spatial spectrum) [8]. Opposed to [5,6], the spatial spectrum was constructed from time-frequency (TF) bins where one speaker was assumed to be dominant over all other speakers, noise, and reverberation, solely.…”

Section: Introductionmentioning

confidence: 99%

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Comparison of Binaural RTF-Vector-Based Direction of Arrival Estimation Methods Exploiting an External Microphone

Fejgin

Doclo

2021

2021 29th European Signal Processing Conference (EUSIPCO)

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Recently, a relative transfer function (RTF) vector-based method has been proposed to estimate the direction of arrival (DOA) of a target speaker for a binaural hearing aid setup, assuming the availability of external microphones. This method exploits the external microphones to estimate the RTF vector corresponding to the binaural hearing aid and constructs a one-dimensional spatial spectrum by comparing the estimated RTF vector against a database of anechoic prototype RTF vectors for several directions. In this paper, we assume the availability of a calibrated array of external microphones, which is characterized by a second database of anechoic prototype RTF vectors. We propose a method where the external microphones are not only exploited for RTF vector estimation but also assist in estimating the DOA of the target speaker. Based on the estimated RTF vector for all microphones and the prototype RTF databases of the binaural hearing aid and the external microphone array, a two-dimensional spatial spectrum is constructed from which the DOA is estimated. Experimental results for a reverberant environment with diffuse-like noise show that assisted DOA estimation outperforms DOA estimation where the prototype database characterizing the external microphone array is not used.

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Section: Rtf-vector-based Doa Estimationmentioning

confidence: 99%

Section: Rtf-vector-based Doa Estimationmentioning

confidence: 99%