Effect of temporal envelope smearing on speech reception

Drullman, Rob; Festen, Joost Μ.; Plomp, R.

doi:10.1121/1.408467

Cited by 728 publications

(493 citation statements)

References 19 publications

(12 reference statements)

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“…Fast compression has deleterious effects for several reasons. First, important information in speech is carried in the patterns of amplitude modulation in different frequency bands (41,42). Fast compression reduces the modulation depth (43), and this adversely affects speech intelligibility when the compression ratio is greater than approximately 2, at least for normally hearing listeners (44,45).…”

Section: Coding In Cochlear Implantsmentioning

confidence: 99%

Coding of Sounds in the Auditory System and Its Relevance to Signal Processing and Coding in Cochlear Implants

Moore

2003

Otology & Neurotology

146

127

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Objective: To review how the properties of sounds are "coded" in the normal auditory system and to discuss the extent to which cochlear implants can and do represent these codes. Data Sources: Data are taken from published studies of the response of the cochlea and auditory nerve to simple and complex stimuli, in both the normal and the electrically stimulated ear. Review Content: The review describes: 1) the coding in the normal auditory system of overall level (which partly determines perceived loudness), spectral shape (which partly determines perceived timbre and the identity of speech sounds), periodicity (which partly determines pitch), and sound location; 2) the role of the active mechanism in the cochlea, and particularly the fast-acting compression associated with that mechanism; 3) the neural response patterns evoked by cochlear implants; and 4) how the response patterns evoked by implants differ from those observed in the normal auditory system in response to sound. A series of specific issues is then discussed, including: 1) how to compensate for the loss of cochlear compression; 2) the effective number of independent channels in a normal ear and in cochlear implantees; 3) the importance of independence of responses across neurons; 4) the stochastic nature of normal neural responses; 5) the possible role of across-channel coincidence detection; and 6) potential benefits of binaural implantation. Conclusions: Current cochlear implants do not adequately reproduce several aspects of the neural coding of sound in the normal auditory system. Improved electrode arrays and coding systems may lead to improved coding and, it is hoped, to better performance.

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Section: Coding In Cochlear Implantsmentioning

confidence: 99%

Coding of Sounds in the Auditory System and Its Relevance to Signal Processing and Coding in Cochlear Implants

Moore

2003

Otology & Neurotology

146

127

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“…Modulation spectrum features (ModSpec): We tried to capture the rhythm and the repetitive syllable sounds of laughter, which may differ from speech: Bickley and Hunnicutt (1992) and Bachorowski et al (2001) report syllable rates of 4.7 syllables/s and 4.37 syllables/s respectively while in normal speech, the modulation spectrum exhibits a peak at around 3-4 Hz, reflecting the average syllable rate in speech (Drullman et al, 1994). Thus, it appears that the rate of syllable production is somewhat higher in laughter than in conversational speech.…”

Section: Utterance-level Features (Fixed-length Feature Vectors)mentioning

confidence: 99%

Automatic discrimination between laughter and speech

Truong¹,

Leeuwen²

2007

Speech Communication

132

118

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Emotions can be recognized by audible paralinguistic cues in speech. By detecting these paralinguistic cues that can consist of laughter, a trembling voice, coughs, changes in the intonation contour etc., information about the speaker's state and emotion can be revealed. This paper describes the development of a gender-independent laugh detector with the aim to enable automatic emotion recognition. Different types of features (spectral, prosodic) for laughter detection were investigated using different classification techniques (Gaussian Mixture Models, Support Vector Machines, Multi Layer Perceptron) often used in language and speaker recognition. Classification experiments were carried out with short pre-segmented speech and laughter segments extracted from the ICSI Meeting Recorder Corpus (with a mean duration of approximately 2 s). Equal error rates of around 3% were obtained when tested on speaker-independent speech data. We found that a fusion between classifiers based on Gaussian Mixture Models and classifiers based on Support Vector Machines increases discriminative power. We also found that a fusion between classifiers that use spectral features and classifiers that use prosodic information usually increases the performance for discrimination between laughter and speech. Our acoustic measurements showed differences between laughter and speech in mean pitch and in the ratio of the durations of unvoiced to voiced portions, which indicate that these prosodic features are indeed useful for discrimination between laughter and speech.

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“…[2,3]). Speech intelligibility is strongly dependent on modulation rates below 20 Hz, for both amplitude modulation [4,5] and frequency modulation components of speech [6].…”

Section: A Modulation Sensitivitymentioning

confidence: 99%

Magnetoencephalography and Auditory Neural Representations

Simon

Ding

2010

IFMBE Proceedings

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Abstract-Complex sounds, especially natural sounds, can be parametrically characterized by many acoustic and perceptual features, one among which is temporal modulation. Temporal modulations describe changes of a sound in amplitude (amplitude modulation, AM) or in frequency (frequency modulation, FM). AM and FM are fundamental components of communication sounds, such as human speech and speciesspecific vocalizations, as well as music. Temporal modulations are encoded in at least two ways, temporal coding and rate coding. Magnetoencephalography (MEG), with its high temporal resolution and simultaneous access to multiple auditory cortical areas, is a non-invasive tool that can measure and describe the temporal coding of auditory modulations. We refer to the neural temporal encoding of temporal acoustic modulations as "modulation encoding". For simple, individually presented, acoustic modulations, modulation encoding is well described by a simple modulation transfer function (MTF). Even in this simple case, however, the MTF may depend strongly on the type of modulation being encoded (e.g. AM vs. FM, narrowband vs. broadband) or the context in which the modulation is heard (e.g. attended vs. unattended).Here we present a range of different types of modulation encoding employed by human auditory cortex. The simplest examples are for sinusoidally amplitude modulated carriers of a range of bandwidths (with special emphasis on those modulation rates relevant to speech and other natural sounds: below a few tens of Hz). We provide evidence that the modulation transfer functions are lowpass in shape and relatively independent of bandwidth. When several modulations are applied concurrently however, the modulation encoding typically, but not always, becomes non-linear: the auditory modulations are at the rates of the acoustic modulations but also at the rates of cross-modulation frequencies. The physiological occurrence, or not, of these cross terms seem be in accord with the psychophysical concept of modulation filterbanks.

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Effect of temporal envelope smearing on speech reception

Cited by 728 publications

References 19 publications

Coding of Sounds in the Auditory System and Its Relevance to Signal Processing and Coding in Cochlear Implants

Coding of Sounds in the Auditory System and Its Relevance to Signal Processing and Coding in Cochlear Implants

Automatic discrimination between laughter and speech

Magnetoencephalography and Auditory Neural Representations

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