WO2023214571A1 - Procédé et système de formation de faisceaux - Google Patents

Procédé et système de formation de faisceaux Download PDF

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Publication number
WO2023214571A1
WO2023214571A1 PCT/JP2023/017083 JP2023017083W WO2023214571A1 WO 2023214571 A1 WO2023214571 A1 WO 2023214571A1 JP 2023017083 W JP2023017083 W JP 2023017083W WO 2023214571 A1 WO2023214571 A1 WO 2023214571A1
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WO
WIPO (PCT)
Prior art keywords
filter
mvdr
beamforming
signal
input
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Application number
PCT/JP2023/017083
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English (en)
Japanese (ja)
Inventor
信彦 昼間
洋一 藤坂
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リオン株式会社
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Application filed by リオン株式会社 filed Critical リオン株式会社
Publication of WO2023214571A1 publication Critical patent/WO2023214571A1/fr

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    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
    • G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
    • G10L21/0208—Noise filtering
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
    • G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
    • G10L21/0272—Voice signal separating
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
    • G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
    • G10L21/0272—Voice signal separating
    • G10L21/0308—Voice signal separating characterised by the type of parameter measurement, e.g. correlation techniques, zero crossing techniques or predictive techniques

Definitions

  • Binaural beamforming using MVDR is an algorithm that is guaranteed to preserve the desired audio spatial information.
  • this algorithm it is known that when this algorithm is used, the spatial information of the noise is distorted, and the noise is perceived as coming from the same direction as the desired voice (see, for example, Non-Patent Document 1).
  • the present invention employs the following beamforming method and a beamforming system (beamforming device) to which this method is applied. Note that the following words in parentheses are merely examples, and the present invention is not limited thereto.
  • the beamforming method of the fifth aspect various gain calculations are performed for each frequency band in the frequency domain on the second signal path branched from the first signal path, and in this process, the MVDR Gain is also applied. Since coefficients based on the results are calculated on the second signal path and supplied to the FIR filter on the first signal path, according to the beamforming method of the fifth aspect, there is no delay due to analysis and synthesis. , the filtering can be accomplished by an FIR filter on the first signal path. As a result, beamforming with lower delay and more natural hearing can be achieved.
  • FIG. 1 is a block diagram schematically showing a configuration example of a binaural hearing device 100 including a binaural beamformer 1 according to an embodiment.
  • FIG. 2 is a diagram showing an example of a basic configuration of binaural beamforming.
  • FIG. 3 is a diagram more specifically illustrating a basic configuration example of binaural beamforming.
  • FIG. 2 is a block diagram showing in detail a configuration example of a binaural hearing device 100 with two input channels. It is a figure showing an example of the flow of processing in a filter bank of an embodiment.
  • FIG. 7 is a diagram (1/3) showing an example of the flow of processing in a filter bank of a comparative example.
  • the sound input section 10 is a microphone, and converts the sound input into the plurality of microphones into an electrical signal (hereinafter, this signal is referred to as an "input signal"), and sends it to the signal processing section 20.
  • the binaural beamformer 1 performs various signal processing including beamforming using MVDR on the input signal of each microphone, and outputs the processed signal to the sound output section 30.
  • the MVDR-IC algorithm is applied to the binaural beamformer 1. Note that details of the MVDR filter will be described in detail later.
  • the sound output section 30 is a microphone or a speaker, and converts the signals for the left and right channels output from the binaural beamformer 1 into sound and outputs the sound to the outside.
  • the signal processing unit 20 can be implemented, for example, by signal processing by a processor such as a DSP (digital signal processor).
  • N indicates the number of input channels.
  • MVDR is an optimal filter for minimizing distortion of the audio signal
  • the problem is that noise signals are also perceived as coming from the same direction as the audio signal.
  • the above-mentioned non-patent document 4 states that in a diffuse noisy environment, when the desired speech component and the noise component both arrive from the same direction, the SRT corresponding to 50% speech intelligibility does not improve. It has been reported that Therefore, the binaural beamformer 1 employs an MVDR-IC that holds an IC in order to spatially separate the output audio component and the residual noise component.
  • the cost function J of MVDR- IC can be expressed by the following formula.

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  • Engineering & Computer Science (AREA)
  • Computational Linguistics (AREA)
  • Quality & Reliability (AREA)
  • Signal Processing (AREA)
  • Health & Medical Sciences (AREA)
  • Audiology, Speech & Language Pathology (AREA)
  • Human Computer Interaction (AREA)
  • Physics & Mathematics (AREA)
  • Acoustics & Sound (AREA)
  • Multimedia (AREA)
  • Circuit For Audible Band Transducer (AREA)

Abstract

Dans un formeur de faisceaux binaural (1) auquel est appliqué un algorithme pour MVDR-IC, un paramètre pour commander un compromis entre la préservation d'IC d'une composante de bruit provoquée par cet algorithme et la suppression de bruit peut être réglé depuis l'extérieur, afin de permettre à un utilisateur de régler le paramètre lui-même ou automatiquement, en fonction d'un environnement auditif et d'obtenir une formation de faisceaux appropriée.
PCT/JP2023/017083 2022-05-06 2023-05-01 Procédé et système de formation de faisceaux WO2023214571A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
JP2022076676A JP2023165528A (ja) 2022-05-06 2022-05-06 ビームフォーミング方法、ビームフォーミングシステム
JP2022-076676 2022-05-06

Publications (1)

Publication Number Publication Date
WO2023214571A1 true WO2023214571A1 (fr) 2023-11-09

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PCT/JP2023/017083 WO2023214571A1 (fr) 2022-05-06 2023-05-01 Procédé et système de formation de faisceaux

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WO (1) WO2023214571A1 (fr)

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2007123052A1 (fr) * 2006-04-20 2007-11-01 Nec Corporation Dispositif, procédé et programme de commande de réseau adaptatif et dispositif, procédé et programme associés de traitement de réseau adaptatif
US20180330726A1 (en) * 2017-05-15 2018-11-15 Baidu Online Network Technology (Beijing) Co., Ltd Speech recognition method and device based on artificial intelligence

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2007123052A1 (fr) * 2006-04-20 2007-11-01 Nec Corporation Dispositif, procédé et programme de commande de réseau adaptatif et dispositif, procédé et programme associés de traitement de réseau adaptatif
US20180330726A1 (en) * 2017-05-15 2018-11-15 Baidu Online Network Technology (Beijing) Co., Ltd Speech recognition method and device based on artificial intelligence

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
DANIEL MARQUARDT ; SIMON DOCLO: "Interaural Coherence Preservation for Binaural Noise Reduction Using Partial Noise Estimation and Spectral Postfiltering", ARXIV:1806.04885V2, vol. 26, no. 7, 1 July 2018 (2018-07-01), pages 1257 - 1270, XP058403498, DOI: 10.1109/TASLP.2018.2823081 *
HIRUMA NOBUHIKO, FUJISAKA YOH-ICHI, MURAYAMA YOSHITAKA, CO RION, JAPAN TOKYO, CEAR ), JAPAN INC TOKYO: "Low-Latency Real-Time Binaural MVDR-IC for Hearing Assistive Device", CONFERENCE: 2022 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), SHOW & TELL DEMONSTRATIONS, 11 May 2022 (2022-05-11), XP093105739, Retrieved from the Internet <URL: https://www.researchgate.net/profile/Nobuhiko-Hiruma/publication/360514499_Low-latency_real-time_binaural_MVDR-IC_for_hearing_assistive_device> [retrieved on 20231127] *
KATES JAMES M., AREHART KATHRYN HOBERG: "Multichannel Dynamic-Range Compression Using Digital Frequency Warping", EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING, vol. 2005, no. 18, 1 November 2005 (2005-11-01), pages 3003 - 3014, XP093105735, DOI: 10.1155/ASP.2005.3003 *

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