Time-Frequency Masking for Speech Separation and Its Potential for Hearing Aid Design

Wang, DeLiang

doi:10.1177/1084713808326455

Cited by 143 publications

(69 citation statements)

References 71 publications

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“…Listening to suboptimal incoming signal may recruit explicit processing and tax working memory resources Wang, 2008). Individuals with limited working memory capacity may have limited benefit from signal processing because the extra demand for working memory resources imposed by signal processing may exhaust their maximum total resources available.…”

Section: Listening To Processed Speech Signalsmentioning

confidence: 99%

Cognition in Hearing Aid Users: Memory for Everyday Speech

Ng¹

2013

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Hearing impairment interferes with speech communication. Hearing aids are designed to provide amplification for individuals with poor auditory sensitivity. Signal processing algorithms are implemented in hearing aids to further improve speech understanding and to reduce listening effort in noise. When listening effort is reduced, fewer resources are assumed to be needed for speech perception and more resources would thus be freed for cognitive processing of speech. However, this effect has only been reported in young adults with normal hearing, not in hearing aid users. Cognitive abilities, which vary between individuals, have been shown to influence the ability to benefit from hearing aids. Specifically, it is not yet known how individual differences in cognitive abilities interact with signal processing to reduce listening effort. Also, the relationship between cognition and aided speech recognition performance, as a function of acclimatization processes in new hearing aid users, has not been studied previously.This thesis investigated the importance of cognition for speech understanding in experienced and new hearing aid users. Four studies were carried out. In the first three studies (reported in Papers 1 to 3), experienced hearing aid users were tested and the aims were 1) to develop a cognitive test, called the Sentence-final Word Identification and Recall (SWIR) test, to measure the effects of a noise reduction algorithm on processing of highly intelligible speech (everyday sentences). SWIR performance is argued to reflect the amount of remaining resources upon successful speech perception; 2) to investigate, using the SWIR test, whether hearing aid signal processing would affect memory for heard speech; 3) to test whether the effects of signal processing on the ability to recall speech would interact with background noise and individual differences in working memory capacity; and 4) to explore the potential clinical application of the SWIR test by examining the relationship between SWIR performance and self-reported hearing aid outcome. In the fourth study (reported in Paper 4), the aim was 5) to examine the relationship between cognition and speech recognition in noise in new users using various models of hearing aids over the first six months of hearing aid use.Results of the studies reported in Papers 1 and 3 demonstrated that, for experienced users, noise impairs the ability to recall intelligible speech heard in noise. Noise reduction freed up cognitive resources and alleviated the negative impact of noise on memory when speech stimuli were presented in background noise consisting of speech babble spoken in the listener's native language but not in a foreign language. The possible underlying mechanisms are that noise reduction facilitates auditory stream segregation between target and irrelevant speech and reduces the attention captured by the linguistic information in irrelevant speech. In both studies, the effects of noise reduction and SWIR performance were modulated by individual differe...

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Section: Listening To Processed Speech Signalsmentioning

confidence: 99%

Cognition in Hearing Aid Users: Memory for Everyday Speech

Ng¹

2013

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“…Thereupon, at first the modulation spectrum of the speech signal is calculated using the cochlear filtering [11]. Then, the range of pitch frequency of each speaker is determined and finally, this range used for speech segregation.…”

Section: System Descriptionmentioning

confidence: 99%

Single channel speech separation with a frame-based pitch range estimation method in modulation frequency

Mahmoodzadeh

Abutalebi

Soltanian-Zadeh

et al. 2010

2010 5th International Symposium on Telecommunications

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Abstract-Computational Auditory Scene Analysis (CASA) has attracted a lot of interest in segregating speech from monaural mixtures. In this paper, we propose a new method for single channel speech separation with frame-based pitch range estimation in modulation frequency domain. This range is estimated in each frame of modulation spectrum of speech by analyzing onsets and offsets. In the proposed method, target speaker is separated from interfering speaker by filtering the mixture signal with a mask extracted from the modulation spectrogram of mixture signal. Systematic evaluation shows an acceptable level of separation comparing with classic methods.

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“…In studies on speech signals, the separation based on localizations is performed by assuming the W-disjoint orthogonality (W-DO) of sources in the timefrequency (T-F) domain [1]. The localization is the arrival direction of a source signal relative to an observation channel.…”

Section: Introductionmentioning

confidence: 99%

Emphasis of Sound Sources Using Nonnegative Matrix Factorization Based on Stereo Localizations

Mitsukura

2014

Journal of Signal Processing

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In this study, we emphasized sound sources using nonnegative matrix factorization (NMF) with the likelihood of the directions obtained from the estimated localizations. NMF is one of the most commonly used techniques for the separation of music signals. The emphasis of sound sources by NMF has several problems: the uncertainty of the decomposition of the bases corresponding to the sources and the necessity to group the obtained bases according to the sources. These problems have to be solved simultaneously to improve the separation performance. In order to simultaneously solve these problems, we proposed a novel NMF incorporating the cost based on the likelihood of the localizations. According to the experimental results, we could improve the separation performance by using our proposed method.

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Time-Frequency Masking for Speech Separation and Its Potential for Hearing Aid Design

Cited by 143 publications

References 71 publications

Cognition in Hearing Aid Users: Memory for Everyday Speech

Cognition in Hearing Aid Users: Memory for Everyday Speech

Single channel speech separation with a frame-based pitch range estimation method in modulation frequency

Emphasis of Sound Sources Using Nonnegative Matrix Factorization Based on Stereo Localizations

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