Enhancement of speech intelligibility using transients extracted by wavelet packets

Rasetshwane, Daniel M.; Boston, J.R.; Li, Ching-Chung; Durrant, John D.; Genna, Greg

doi:10.1109/aspaa.2009.5346465

Cited by 7 publications

(7 citation statements)

References 12 publications

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“…1. was set to 24, based on modified-rhyme test results [19]. As with Yoo's approach, was used to adjust the modified speech signal so that its energy is equal to the energy of original speech.…”

Section: Transient Emphasis Using Wavelet-packetsmentioning

confidence: 99%

“…Rasetshwanes's method uses wavelet packets to extract an estimate of speech transition components [16]. The speech signal was first high-pass filtered as described above for Yoo's method The signal was then decomposed using wavelet packets based on a Daubechies-18 wavelet to a depth of 4, resulting in 16 packets, each with a sequence of wavelet coefficients.…”

Section: Transient Emphasis Using Wavelet-packetsmentioning

confidence: 99%

“…Recently, Rasetshwane described a processing method based on wavelet-packet analysis that yields results approximating previous results, providing intelligibility improvements of over 20%. [16]. This method uses a fast wavelet transform that can be implemented to run in realtime.…”

Section: Introductionmentioning

confidence: 99%

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Speech enhancement by combination of transient emphasis and noise cancelation

Rasetshwane

Boston

Durrant

et al. 2011

2011 Digital Signal Processing and Signal Processing Education Meeting (DSP/SPE)

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This paper evaluates the effectiveness of combining speech modification techniques that enhance transition components with active noise cancellation to improve the intelligibility of speech in noise. Two speech modification techniques were considered. One is based on wavelet-packet analysis, and the second uses a fixed filter, derived from timefrequency analysis, that emphasizes high frequencies.Active noise cancellation was provided by Bose noisecancelling headphones. The test noise was real, generated by a ground auxiliary generator on the tarmac at an Air National Guard facility. The test signals were speech tokens from the modified rhyme (psycho-acoustic) test, recorded by a male speaker. This paradigm was used to measure word recognition rates at various signal-to-noise ratios. Active noise cancellation by itself provided over 40% increase in word recognition, while the modified speech and fixed filter techniques alone provided up to 20% improvement, depending on the signal-to-noise ratio. In combination, the speech modification approaches provided over 15% additional improvement in intelligibility over noise cancellation alone.

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Section: Transient Emphasis Using Wavelet-packetsmentioning

confidence: 99%

Section: Transient Emphasis Using Wavelet-packetsmentioning

confidence: 99%

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Speech enhancement by combination of transient emphasis and noise cancelation

Rasetshwane

Boston

Durrant

et al. 2011

2011 Digital Signal Processing and Signal Processing Education Meeting (DSP/SPE)

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“…Transient extraction in speech is important for speech processing because it plays a fundamental role in speech sound identification and discrimination [1] [2]. In several speech studies, transients serve as a cue for finding the most informative sections of the speech signal [3] [4].…”

Section: Introductionmentioning

confidence: 99%

Comparison of skewness-based salient event detector algorithms in speech

Kovács

Kiss

Vicsi

et al. 2015

2015 6th IEEE International Conference on Cognitive Infocommunications (CogInfoCom)

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Abstract-In this work, we compare two skewness-based salient event detector algorithms, which can detect transients in human speech signals. Speech transients are characterized by rapid changes in signal energy. The purpose of this study was to compare the identification of transients by two different methods based on skewness calculation in order to develop a method to be used in studying the processing of speech transients in the human brain. The first method, the skewness in variable time (SKV) finds transients using a cochlear model. The skewness of the energy distribution for a variable time window is implemented on artificial neural networks. The second method, the automatic segmentation method for transient detection (RoT) is more speech segmentation-based and developed for detecting transientspeech segment ratio in spoken records. In the current study, the test corpus included Hungarian and English speech recorded from different speakers (2 male and 2 female for both languages) Results were compared by the F-measure, the Jaccard similarity index, and the Hamming distance. The results of the two algorithms were also tested against a hand-labeled corpus annotated by linguistic experts for an absolute assessment of the performance of the two methods. Transient detection was tested once for onset events alone and, separately, for onset and offset events together. The results show that in most cases, the RoT method works better on the expert labeled databases. Using F measure with +-25ms window length the following results were obtained when all type of transient events were evaluated: 0,664 on English and 0,834 on Hungarian. Otherwise, the two methods identify the same stimulus features as the transients also coinciding with those hand-labeled by experts.

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“…It is even more crucial to focus on these speech parts because the dynamic changes can easily be affected in adverse listening conditions. A number of studies (Hazan and Simpson, 1998;Lorenzi et al, 1999;Apoux et al, 2004;Skowronski and Harris, 2006;Yoo et al, 2007;Rasetshwane et al, 2009) investigated the effect of increasing the CV ratio or amplifying the transient parts of the target speech signal with NH listeners. Amplifying the transient parts lead to an improvement in speech intelligibility in various noisy conditions.…”

Section: Introductionmentioning

confidence: 99%

The potential of onset enhancement for increased speech intelligibility in auditory prostheses

Koning

Wouters

2012

The Journal of the Acoustical Society of America

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Recent studies have shown that transient parts of a speech signal contribute most to speech intelligibility in normal-hearing listeners. In this study, the influence of enhancing the onsets of the envelope of the speech signal on speech intelligibility in noisy conditions using an eight channel cochlear implant vocoder simulation was investigated. The enhanced envelope (EE) strategy emphasizes the onsets of the speech envelope by deriving an additional peak signal at the onsets in each frequency band. A sentence recognition task in stationary speech shaped noise showed a significant speech reception threshold (SRT) improvement of 2.5 dB for the EE in comparison to the reference continuous interleaved sampling strategy and of 1.7 dB when an ideal Wiener filter was used for the onset extraction on the noisy signal. In a competitive talker condition, a significant SRT improvement of 2.6 dB was measured. A benefit was obtained in all experiments with the peak signal derived from the clean speech. Although the EE strategy is not effective in many real-life situations, the results suggest that there is potential for speech intelligibility improvement when an enhancement of the onsets of the speech envelope is included in the signal processing of auditory prostheses.

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Enhancement of speech intelligibility using transients extracted by wavelet packets

Cited by 7 publications

References 12 publications

Speech enhancement by combination of transient emphasis and noise cancelation

Speech enhancement by combination of transient emphasis and noise cancelation

Comparison of skewness-based salient event detector algorithms in speech

The potential of onset enhancement for increased speech intelligibility in auditory prostheses

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