TR2024-026

NIIRF: Neural IIR Filter Field for HRTF Upsampling and Personalization

Abstract:

Head-related transfer functions (HRTFs) are important for immersive audio, and their spatial interpolation has been studied to up- sample finite measurements. Recently, neural fields (NFs) which map from sound source direction to HRTF have gained attention. Existing NF-based methods focused on estimating the magnitude of the HRTF from a given sound source direction, and the magnitude is converted to a finite impulse response (FIR) filter. We propose the neural infinite impulse response filter field (NIIRF) method that instead estimates the coefficients of cascaded IIR filters. IIR filters mimic the modal nature of HRTFs, thus needing fewer coefficients to approximate them well compared to FIR filters. We find that our method can match the performance of existing NF-based methods on multiple datasets, even outperforming them when measurements are sparse. We also explore approaches to personalize the NF to a subject and experimentally find low-rank adaptation to be effective.

 

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  • Related News & Events

    •  AWARD    MERL team wins the Listener Acoustic Personalisation (LAP) 2024 Challenge
      Date: August 29, 2024
      Awarded to: Yoshiki Masuyama, Gordon Wichern, Francois G. Germain, Christopher Ick, and Jonathan Le Roux
      MERL Contacts: François Germain; Jonathan Le Roux; Gordon Wichern
      Research Areas: Artificial Intelligence, Machine Learning, Speech & Audio
      Brief
      • MERL's Speech & Audio team ranked 1st out of 7 teams in Task 2 of the 1st SONICOM Listener Acoustic Personalisation (LAP) Challenge, which focused on "Spatial upsampling for obtaining a high-spatial-resolution HRTF from a very low number of directions". The team was led by Yoshiki Masuyama, and also included Gordon Wichern, Francois Germain, MERL intern Christopher Ick, and Jonathan Le Roux.

        The LAP Challenge workshop and award ceremony was hosted by the 32nd European Signal Processing Conference (EUSIPCO 24) on August 29, 2024 in Lyon, France. Yoshiki Masuyama presented the team's method, "Retrieval-Augmented Neural Field for HRTF Upsampling and Personalization", and received the award from Prof. Michele Geronazzo (University of Padova, IT, and Imperial College London, UK), Chair of the Challenge's Organizing Committee.

        The LAP challenge aims to explore challenges in the field of personalized spatial audio, with the first edition focusing on the spatial upsampling and interpolation of head-related transfer functions (HRTFs). HRTFs with dense spatial grids are required for immersive audio experiences, but their recording is time-consuming. Although HRTF spatial upsampling has recently shown remarkable progress with approaches involving neural fields, HRTF estimation accuracy remains limited when upsampling from only a few measured directions, e.g., 3 or 5 measurements. The MERL team tackled this problem by proposing a retrieval-augmented neural field (RANF). RANF retrieves a subject whose HRTFs are close to those of the target subject at the measured directions from a library of subjects. The HRTF of the retrieved subject at the target direction is fed into the neural field in addition to the desired sound source direction. The team also developed a neural network architecture that can handle an arbitrary number of retrieved subjects, inspired by a multi-channel processing technique called transform-average-concatenate.
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    •  EVENT    MERL Contributes to ICASSP 2024
      Date: Sunday, April 14, 2024 - Friday, April 19, 2024
      Location: Seoul, South Korea
      MERL Contacts: Petros T. Boufounos; François Germain; Chiori Hori; Sameer Khurana; Toshiaki Koike-Akino; Jonathan Le Roux; Hassan Mansour; Kieran Parsons; Joshua Rapp; Anthony Vetro; Pu (Perry) Wang; Gordon Wichern
      Research Areas: Artificial Intelligence, Computational Sensing, Machine Learning, Robotics, Signal Processing, Speech & Audio
      Brief
      • MERL has made numerous contributions to both the organization and technical program of ICASSP 2024, which is being held in Seoul, Korea from April 14-19, 2024.

        Sponsorship and Awards

        MERL is proud to be a Bronze Patron of the conference and will participate in the student job fair on Thursday, April 18. Please join this session to learn more about employment opportunities at MERL, including openings for research scientists, post-docs, and interns.

        MERL is pleased to be the sponsor of two IEEE Awards that will be presented at the conference. We congratulate Prof. Stéphane G. Mallat, the recipient of the 2024 IEEE Fourier Award for Signal Processing, and Prof. Keiichi Tokuda, the recipient of the 2024 IEEE James L. Flanagan Speech and Audio Processing Award.

        Jonathan Le Roux, MERL Speech and Audio Senior Team Leader, will also be recognized during the Awards Ceremony for his recent elevation to IEEE Fellow.

        Technical Program

        MERL will present 13 papers in the main conference on a wide range of topics including automated audio captioning, speech separation, audio generative models, speech and sound synthesis, spatial audio reproduction, multimodal indoor monitoring, radar imaging, depth estimation, physics-informed machine learning, and integrated sensing and communications (ISAC). Three workshop papers have also been accepted for presentation on audio-visual speaker diarization, music source separation, and music generative models.

        Perry Wang is the co-organizer of the Workshop on Signal Processing and Machine Learning Advances in Automotive Radars (SPLAR), held on Sunday, April 14. It features keynote talks from leaders in both academia and industry, peer-reviewed workshop papers, and lightning talks from ICASSP regular tracks on signal processing and machine learning for automotive radar and, more generally, radar perception.

        Gordon Wichern will present an invited keynote talk on analyzing and interpreting audio deep learning models at the Workshop on Explainable Machine Learning for Speech and Audio (XAI-SA), held on Monday, April 15. He will also appear in a panel discussion on interpretable audio AI at the workshop.

        Perry Wang also co-organizes a two-part special session on Next-Generation Wi-Fi Sensing (SS-L9 and SS-L13) which will be held on Thursday afternoon, April 18. The special session includes papers on PHY-layer oriented signal processing and data-driven deep learning advances, and supports upcoming 802.11bf WLAN Sensing Standardization activities.

        Petros Boufounos is participating as a mentor in ICASSP’s Micro-Mentoring Experience Program (MiME).

        About ICASSP

        ICASSP is the flagship conference of the IEEE Signal Processing Society, and the world's largest and most comprehensive technical conference focused on the research advances and latest technological development in signal and information processing. The event attracts more than 3000 participants.
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  • Related Publication

  •  Masuyama, Y., Wichern, G., Germain, F.G., Pan, Z., Khurana, S., Hori, C., Le Roux, J., "NIIRF: Neural IIR Filter Field for HRTF Upsampling and Personalization", arXiv, February 2024.
    BibTeX arXiv
    • @article{Masuyama2024feb,
    • author = {Masuyama, Yoshiki and Wichern, Gordon and Germain, François G and Pan, Zexu and Khurana, Sameer and Hori, Chiori and Le Roux, Jonathan},
    • title = {NIIRF: Neural IIR Filter Field for HRTF Upsampling and Personalization},
    • journal = {arXiv},
    • year = 2024,
    • month = feb,
    • url = {https://arxiv.org/abs/2402.17907}
    • }