Literature DB >> 27794330

Predicting speech intelligibility based on a correlation metric in the envelope power spectrum domain.

Helia Relaño-Iborra1, Tobias May1, Johannes Zaar1, Christoph Scheidiger1, Torsten Dau1.   

Abstract

A speech intelligibility prediction model is proposed that combines the auditory processing front end of the multi-resolution speech-based envelope power spectrum model [mr-sEPSM; Jørgensen, Ewert, and Dau (2013). J. Acoust. Soc. Am. 134(1), 436-446] with a correlation back end inspired by the short-time objective intelligibility measure [STOI; Taal, Hendriks, Heusdens, and Jensen (2011). IEEE Trans. Audio Speech Lang. PROCESS: 19(7), 2125-2136]. This "hybrid" model, named sEPSMcorr, is shown to account for the effects of stationary and fluctuating additive interferers as well as for the effects of non-linear distortions, such as spectral subtraction, phase jitter, and ideal time frequency segregation (ITFS). The model shows a broader predictive range than both the original mr-sEPSM (which fails in the phase-jitter and ITFS conditions) and STOI (which fails to predict the influence of fluctuating interferers), albeit with lower accuracy than the source models in some individual conditions. Similar to other models that employ a short-term correlation-based back end, including STOI, the proposed model fails to account for the effects of room reverberation on speech intelligibility. Overall, the model might be valuable for evaluating the effects of a large range of interferers and distortions on speech intelligibility, including consequences of hearing impairment and hearing-instrument signal processing.

Entities:  

Year:  2016        PMID: 27794330     DOI: 10.1121/1.4964505

Source DB:  PubMed          Journal:  J Acoust Soc Am        ISSN: 0001-4966            Impact factor:   1.840


  8 in total

1.  A harmonic-cancellation-based model to predict speech intelligibility against a harmonic masker.

Authors:  Luna Prud'homme; Mathieu Lavandier; Virginia Best
Journal:  J Acoust Soc Am       Date:  2020-11       Impact factor: 1.840

2.  Understanding degraded speech leads to perceptual gating of a brainstem reflex in human listeners.

Authors:  Heivet Hernández-Pérez; Jason Mikiel-Hunter; David McAlpine; Sumitrajit Dhar; Sriram Boothalingam; Jessica J M Monaghan; Catherine M McMahon
Journal:  PLoS Biol       Date:  2021-10-20       Impact factor: 8.029

3.  Temporal fine structure influences voicing confusions for consonant identification in multi-talker babble.

Authors:  Vibha Viswanathan; Barbara G Shinn-Cunningham; Michael G Heinz
Journal:  J Acoust Soc Am       Date:  2021-10       Impact factor: 2.482

4.  Modulation masking and fine structure shape neural envelope coding to predict speech intelligibility across diverse listening conditions.

Authors:  Vibha Viswanathan; Hari M Bharadwaj; Barbara G Shinn-Cunningham; Michael G Heinz
Journal:  J Acoust Soc Am       Date:  2021-09       Impact factor: 2.482

5.  Speech Categorization Reveals the Role of Early-Stage Temporal-Coherence Processing in Auditory Scene Analysis.

Authors:  Vibha Viswanathan; Barbara G Shinn-Cunningham; Michael G Heinz
Journal:  J Neurosci       Date:  2021-11-11       Impact factor: 6.709

6.  Predicting Speech Intelligibility Based on Across-Frequency Contrast in Simulated Auditory-Nerve Fluctuations.

Authors:  Christoph Scheidiger; Laurel H Carney; Torsten Dau; Johannes Zaar
Journal:  Acta Acust United Acust       Date:  2018 Sep-Oct

7.  Spectrally specific temporal analyses of spike-train responses to complex sounds: A unifying framework.

Authors:  Satyabrata Parida; Hari Bharadwaj; Michael G Heinz
Journal:  PLoS Comput Biol       Date:  2021-02-22       Impact factor: 4.475

8.  Transient Noise Reduction Using a Deep Recurrent Neural Network: Effects on Subjective Speech Intelligibility and Listening Comfort.

Authors:  Mahmoud Keshavarzi; Tobias Reichenbach; Brian C J Moore
Journal:  Trends Hear       Date:  2021 Jan-Dec       Impact factor: 3.293

  8 in total

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