Unsupervised Low Latency Speech Enhancement With RT-GCC-NMF

Sean U.N. Wood*, Jean Rouat

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


In this paper, we present RT-GCC-NMF: a real-time (RT), two-channel blind speech enhancement algorithm that combines the non-negative matrix factorization (NMF) dictionary learning algorithm with the generalized cross-correlation (GCC) spatial localization method. Using a pre-learned universal NMF dictionary, RT-GCC-NMF operates in a frame-by-frame fashion by associating individual dictionary atoms to target speech or background interference based on their estimated time-delay of arrivals. We evaluate RT-GCC-NMF on two-channel mixtures of speech and real-world noise from the signal separation and evaluation campaign (SiSEC). We demonstrate that this approach generalizes to new speakers, acoustic environments, and recording setups from very little training data, and outperforms all but one of the algorithms from the SiSEC challenge in terms of overall perceptual evaluation methods for audio source separation (PEASS) scores and compares favourably to the ideal binary mask baseline. Over a wide range of input signal to noise ratios (SNRs), we show that this approach simultaneously improves the PEASS and SNR-based blind source separation eval objective quality metrics as well as the short-time objective intelligibility (STOI) and extended STOI objective speech intelligibility metrics. A flexible, soft masking function in the space of NMF activation coefficients offers real-time control of the tradeoff between interference suppression and target speaker fidelity. Finally, we use an asymmetric short-time Fourier transform to reduce the inherent algorithmic latency of RT-GCC-NMF from 64 ms to 2 ms with no loss in performance. We demonstrate that latencies within the tolerable range for hearing AIDS are possible on current hardware platforms.

Original languageEnglish
Article number8681078
Pages (from-to)332-346
Number of pages15
JournalIEEE Journal on Selected Topics in Signal Processing
Issue number2
Publication statusPublished - 1 May 2019


  • GCC
  • low latency
  • multi-channel
  • NMF
  • phase-based
  • real-time systems
  • source separation
  • speech enhancement
  • Unsupervised machine learning

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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