Spectral Contrast Effects Research Articles

The effects of variability on context effects and psychometric function slopes in speaking rate normalizationa).

Acoustic context influences speech perception, but contextual variability restricts this influence. Assgari and Stilp [J. Acoust. Soc. Am. 138, 3023-3032 (2015)] demonstrated that when categorizing vowels, variability in who spoke the preceding context sentence on each trial but not the sentence contents diminished the resulting spectral contrast effects (perceptual shifts in categorization stemming from spectral differences between sounds). Yet, how such contextual variability affects temporal contrast effects (TCEs) (also known as speaking rate normalization; categorization shifts stemming from temporal differences) is unknown. Here, stimuli were the same context sentences and conditions (one talker saying one sentence, one talker saying 200 sentences, 200 talkers saying 200 sentences) used in Assgari and Stilp [J. Acoust. Soc. Am. 138, 3023-3032 (2015)], but set to fast or slow speaking rates to encourage perception of target words as "tier" or "deer," respectively. In Experiment 1, sentence variability and talker variability each diminished TCE magnitudes; talker variability also produced shallower psychometric function slopes. In Experiment 2, when speaking rates were matched across the 200-sentences conditions, neither TCE magnitudes nor slopes differed across conditions. In Experiment 3, matching slow and fast rates across all conditions failed to produce equal TCEs and slopes everywhere. Results suggest a complex interplay between acoustic, talker, and sentence variability in shaping TCEs in speech perception.

The influences of forward context on stop-consonant perception: The combined effects of contrast and acoustic cue activation?

The perception of the /da/-/ga/ series, distinguished primarily by the third formant (F3) transition, is affected by many nonspeech and speech sounds. Previous studies mainly investigated the influences of context stimuli with frequency bands located in the F3 region and proposed the account of spectral contrast effects. This study examined the effects of context stimuli with bands not in the F3 region. The results revealed that these non-F3-region stimuli (whether with bands higher or lower than the F3 region) mainly facilitated the identification of /ga/; for example, the stimuli (including frequency-modulated glides, sine-wave tones, filtered sentences, and natural vowels) in the low-frequency band (500-1500 Hz) led to more /ga/ responses than those in the low-F3 region (1500-2500 Hz). It is suggested that in the F3 region, context stimuli may act through spectral contrast effects, while in non-F3 regions, context stimuli might activate the acoustic cues of /g/ and further facilitate the identification of /ga/. The combination of contrast and acoustic cue effects can explain more results concerning the forward context influences on the perception of the /da/-/ga/ series, including the effects of non-F3-region stimuli and the imbalanced influences of context stimuli on /da/ and /ga/ perception.

Short-term, not long-term, average spectra of preceding sentences bias consonant categorization.

Speech sound perception is influenced by the spectral properties of surrounding sounds. For example, listeners perceive /g/ (lower F3 onset) more often after sounds with prominent high-F3 frequencies and perceive /d/ (higher F3 onset) more often after sounds with prominent low-F3 frequencies. These biases are known as spectral contrast effects (SCEs). Much of this work examined differences between long-term average spectra (LTAS) of preceding sounds and target speech sounds. Post hoc analyses by Stilp and Assgari [(2021) Atten. Percept. Psychophys. 83(6) 2694-2708] revealed that spectra of the last 475 ms of precursor sentences, not the entire LTAS, best predicted biases in consonant categorization. Here, the influences of proximal (last 500 ms) versus distal (before the last 500 ms) portions of precursor sentences on subsequent consonant categorization were compared. Sentences emphasized different frequency regions in each temporal window (e.g., distal low-F3 emphasis, proximal high-F3 emphasis, and vice versa) naturally or via filtering. In both cases, shifts in consonant categorization were produced in accordance with spectral properties of the proximal window. This was replicated when the distal window did not emphasize either frequency region, but the proximal window did. Results endorse closer consideration of patterns of spectral energy over time in preceding sounds, not just their LTAS.

Testing the role of primary musical instrument on context effects in music perception

Musicians display numerous perceptual benefits versus nonmusicians, such as better pitch and melody perception (the “musician advantage”). Recently, Shorey et al. (2021 ASA) investigated whether this musician advantage extended to spectral contrast effects (SCEs; categorization shifts produced by acoustic properties of surrounding sounds) in musical instrument recognition. Musicians and nonmusicians listened to a context sound (filtered string quartet passage highlighting frequencies of the horn or saxophone), then categorized a target sound (tone from a six-step series varying from horn to saxophone). Although musicians displayed superior pitch discrimination, their SCEs did not differ from those of nonmusicians. Importantly, separate research has reported that a musician’s instrument of training heavily influences musical perception, potentially improving frequency discrimination and rhythm perception/production. However, in the Shorey et al. study, musicians were recruited without respect to their primary instrument. This follow-up study uses the same methodology as Shorey et al. but recruits only musicians who play horn or saxophone (the instruments used as target sounds) as their primary instrument. It is predicted that horn and saxophone players will display larger SCEs than nonmusicians due to their intimate familiarity with the instrument timbres. Preliminary data are trending in the predicted direction; full results will be discussed.

Context effects in perception of vowels differentiated by F1 are not influenced by variability in talkers' mean F1 or F3.

Spectral properties of earlier sounds (context) influence recognition of later sounds (target). Acoustic variability in context stimuli can disrupt this process. When mean fundamental frequencies (f0's) of preceding context sentences were highly variable across trials, shifts in target vowel categorization [due to spectral contrast effects (SCEs)] were smaller than when sentence mean f0's were less variable; when sentences were rearranged to exhibit high or low variability in mean first formant frequencies (F1) in a given block, SCE magnitudes were equivalent [Assgari, Theodore, and Stilp (2019) J. Acoust. Soc. Am. 145(3), 1443-1454]. However, since sentences were originally chosen based on variability in mean f0, stimuli underrepresented the extent to which mean F1 could vary. Here, target vowels (/ɪ/-/ɛ/) were categorized following context sentences that varied substantially in mean F1 (experiment 1) or mean F3 (experiment 2) with variability in mean f0 held constant. In experiment 1, SCE magnitudes were equivalent whether context sentences had high or low variability in mean F1; the same pattern was observed in experiment 2 for new sentences with high or low variability in mean F3. Variability in some acoustic properties (mean f0) can be more perceptually consequential than others (mean F1, mean F3), but these results may be task-dependent.

Parameterizing spectral contrast effects in vowel categorization using noise contexts.

When spectra differ between earlier (context) and later (target) sounds, listeners perceive larger spectral changes than are physically present. When context sounds (e.g., a sentence) possess relatively higher frequencies, the target sound (e.g., a vowel sound) is perceived as possessing relatively lower frequencies, and vice versa. These spectral contrast effects (SCEs) are pervasive in auditory perception, but studies traditionally employed contexts with high spectrotemporal variability that made it difficult to understand exactly when context spectral properties biased perception. Here, contexts were speech-shaped noise divided into four consecutive 500-ms epochs. Contexts were filtered to amplify low-F1 (100-400 Hz) or high-F1 (550-850 Hz) frequencies to encourage target perception of /ɛ/ ("bet") or /ɪ/ ("bit"), respectively, via SCEs. Spectral peaks in the context ranged from its initial epoch(s) to its entire duration (onset paradigm), ranged from its final epoch(s) to its entire duration (offset paradigm), or were present for only one epoch (single paradigm). SCE magnitudes increased as spectral-peak durations increased and/or occurred later in the context (closer to the target). Contrary to predictions, brief early spectral peaks still biased subsequent target categorization. Results are compared to related experiments using speech contexts, and physiological and/or psychoacoustic idiosyncrasies of the noise contexts are considered.

Spectral Contrast Effects Reveal Different Acoustic Cues for Vowel Recognition in Cochlear-Implant Users.

The identity of a speech sound can be affected by the spectrum of a preceding stimulus in a contrastive manner. Although such aftereffects are often reduced in people with hearing loss and cochlear implants (CIs), one recent study demonstrated larger spectral contrast effects in CI users than in normal-hearing (NH) listeners. The present study aimed to shed light on this puzzling finding. We hypothesized that poorer spectral resolution leads CI users to rely on different acoustic cues not only to identify speech sounds but also to adapt to the context. Thirteen postlingually deafened adult CI users and 33 NH participants (listening to either vocoded or unprocessed speech) participated in this study. Psychometric functions were estimated in a vowel categorization task along the /I/ to /ε/ (as in "bit" and "bet") continuum following a context sentence, the long-term average spectrum of which was manipulated at the level of either fine-grained local spectral cues or coarser global spectral cues. In NH listeners with unprocessed speech, the aftereffect was determined solely by the fine-grained local spectral cues, resulting in a surprising insensitivity to the larger, global spectral cues utilized by CI users. Restricting the spectral resolution available to NH listeners via vocoding resulted in patterns of responses more similar to those found in CI users. However, the size of the contrast aftereffect remained smaller in NH listeners than in CI users. Only the spectral contrasts used by listeners contributed to the spectral contrast effects in vowel identification. These results explain why CI users can experience larger-than-normal context effects under specific conditions. The results also suggest that adaptation to new spectral cues can be very rapid for vowel discrimination, but may follow a longer time course to influence spectral contrast effects.

Natural music context biases musical instrument categorization.

Perception of sounds occurs in the context of surrounding sounds. When spectral properties differ between earlier (context) and later (target) sounds, categorization of later sounds becomes biased through spectral contrast effects (SCEs). Past research has shown SCEs to bias categorization of speech and music alike. Recent studies have extended SCEs to naturalistic listening conditions when the inherent spectral composition of (unfiltered) sentences biased speech categorization. Here, we tested whether natural (unfiltered) music would similarly bias categorization of French horn and tenor saxophone targets. Preceding contexts were either solo performances of the French horn or tenor saxophone (unfiltered; 1 secondduration in Experiment 1, or 3 seconds durationin Experiment 2) or a string quintet processed to emphasize frequencies in the horn or saxophone (filtered; 1 secondduration). Both approaches produced SCEs, producing more "saxophone" responses following horn/ horn-like contexts and vice versa. One-second filtered contexts produced SCEs as in previous studies, but 1-second unfiltered contexts did not. Three-second unfiltered contexts biased perception, but to a lesser degree than filtered contexts did. These results extend SCEs in musical instrument categorization to everyday listening conditions.

Spectral contrast effects and auditory enhancement under normal and impaired hearing.

We are generally able to identify sounds and understand speech with ease, despite the large variations in the acoustics of each sound, which occur due to factors such as different talkers, background noise, and room acoustics. This form of perceptual constancy is likely to be mediated in part by the auditory system's ability to adapt to the ongoing environment or context in which sounds are presented. Auditory context effects have been studied under different names, such as spectral contrast effects in speech and auditory enhancement effects in psychoacoustics, but they share some important properties and may be mediated by similar underlying neural mechanisms. This review provides a survey of recent studies from our laboratory that investigate the mechanisms of speech spectral contrast effects and auditory enhancement in people with normal hearing, hearing loss, and cochlear implants. We argue that a better understanding of such context effects in people with normal hearing may allow us to restore some of these important effects for people with hearing loss via signal processing in hearing aids and cochlear implants, thereby potentially improving auditory and speech perception in the complex and variable everyday acoustic backgrounds that surround us.

Auditory enhancement and spectral contrast effects in speech perception.

The auditory system is remarkably sensitive to changes in the acoustic environment. This is exemplified by two classic effects of preceding spectral context on perception. In auditory enhancement effects (EEs), the absence and subsequent insertion of a frequency component increases its salience. In spectral contrast effects (SCEs), spectral differences between earlier and later (target) sounds are perceptually magnified, biasing target sound categorization. These effects have been suggested to be related, but have largely been studied separately. Here, EEs and SCEs are demonstrated using the same speech materials. In Experiment 1, listeners categorized vowels (/ɪ/-/ɛ/) or consonants (/d/-/g/) following a sentence processed by a bandpass or bandstop filter (vowel tasks: 100-400 or 550-850 Hz; consonant tasks: 1700-2700 or 2700-3700 Hz). Bandpass filtering produced SCEs and bandstop filtering produced EEs, with effect magnitudes significantly correlated at the individual differences level. In Experiment 2, context sentences were processed by variable-depth notch filters in these frequency regions (-5 to -20 dB). EE magnitudes increased at larger notch depths, growing linearly in consonant categorization. This parallels previous research where SCEs increased linearly for larger spectral peaks in the context sentence. These results link EEs and SCEs, as both shape speech categorization in orderly ways.

Spectral contrast effects are modulated by selective attention in \u201ccocktail party\u201d settings

Speech sounds are perceived relative to spectral properties of surrounding speech. For instance, target words that are ambiguous between /bɪt/ (with low F1) and /bɛt/ (with high F1) are more likely to be perceived as “bet” after a “low F1” sentence, but as “bit” after a “high F1” sentence. However, it is unclear how these spectral contrast effects (SCEs) operate in multi-talker listening conditions. Recently, Feng and Oxenham (J.Exp.Psychol.-Hum.Percept.Perform. 44(9), 1447–1457, 2018b) reported that selective attention affected SCEs to a small degree, using two simultaneously presented sentences produced by a single talker. The present study assessed the role of selective attention in more naturalistic “cocktail party” settings, with 200 lexically unique sentences, 20 target words, and different talkers. Results indicate that selective attention to one talker in one ear (while ignoring another talker in the other ear) modulates SCEs in such a way that only the spectral properties of the attended talker influences target perception. However, SCEs were much smaller in multi-talker settings (Experiment 2) than those in single-talker settings (Experiment 1). Therefore, the influence of SCEs on speech comprehension in more naturalistic settings (i.e., with competing talkers) may be smaller than estimated based on studies without competing talkers.

Earlier music biases subsequent musical instrument categorization

Perception of sounds occurs in the context of surrounding sounds. When spectral properties differ between earlier (context) and later (target) sounds, categorization of later sounds becomes biased through spectral contrast effects (SCEs). Past research has shown SCEs to bias categorization of speech and music alike. Additionally, the magnitudes of SCEs are not all-or-none but vary continuously in both speech and music categorization. Recently, the natural spectral composition of (unfiltered) sentences biased speech categorization via SCEs (Stilp and Assgari, under review). Here, we tested whether natural (unfiltered) music would similarly bias categorization of French horn and tenor saxophone targets. Preceding contexts were either solo performances of the French horn or tenor saxophone (unfiltered) or a string quintet processed to emphasize frequencies in the horn or saxophone (filtered). Categorization was influenced by SCEs in both unfiltered and filtered conditions, with more “saxophone” responses following horn / horn-like contexts and vice versa. Since unfiltered music produced SCEs in musical instrument categorization, this extends their influence to everyday listening conditions.

Variability in talkers' fundamental frequencies shapes context effects in speech perception.

The perception of any given sound is influenced by surrounding sounds. When successive sounds differ in their spectral compositions, these differences may be perceptually magnified, resulting in spectral contrast effects (SCEs). For example, listeners are more likely to perceive /ɪ/ (low F1) following sentences with higher F1 frequencies; listeners are also more likely to perceive /ɛ/ (high F1) following sentences with lower F1 frequencies. Previous research showed that SCEs for vowel categorization were attenuated when sentence contexts were spoken by different talkers [Assgari and Stilp. (2015). J. Acoust. Soc. Am. 138(5), 3023-3032], but the locus of this diminished contextual influence was not specified. Here, three experiments examined implications of variable talker acoustics for SCEs in the categorization of /ɪ/ and /ɛ/. The results showed that SCEs were smaller when the mean fundamental frequency (f0) of context sentences was highly variable across talkers compared to when mean f0 was more consistent, even when talker gender was held constant. In contrast, SCE magnitudes were not influenced by variability in mean F1. These findings suggest that talker variability attenuates SCEs due to diminished consistency of f0 as a contextual influence. Connections between these results and talker normalization are considered.

Musical instrument categorization is highly sensitive to spectral properties of earlier sounds.

Auditory perception is shaped by spectral properties of surrounding sounds. For example, when spectral properties differ between earlier (context) and later (target) sounds, this can produce spectral contrast effects (SCEs; i.e., categorization boundary shifts) that bias perception of later sounds. SCEs affect perception of speech and nonspeech sounds alike (Stilp Alexander, Kiefte, & Kluender in Attention, Perception, & Psychophysics, 72(2), 470-480, 2010). When categorizing speech sounds, SCE magnitudes increased linearly with greater spectral differences between contexts and target sounds (Stilp, Anderson, & Winn in Journal of the Acoustical Society of America, 137(6), 3466-3476, 2015; Stilp & Alexander in Proceedings of Meetings on Acoustics, 26, 2016; Stilp & Assgari in Journal of the Acoustical Society of America, 141(2), EL153-EL158, 2017). The present experiment tested whether this acute context sensitivity generalized to nonspeech categorization. Listeners categorized musical instrument target sounds that varied from French horn to tenor saxophone. Before each target, listeners heard a 1-second string quintet sample processed by filters that reflected part of (25%, 50%, 75%) or the full (100%) difference between horn and saxophone spectra. Larger filter gains increased spectral distinctness across context and target sounds, and resulting SCE magnitudes increased linearly, parallel to speech categorization. Thus, a highly sensitive relationship between context spectra and target categorization appears to be fundamental to auditory perception.

Notches in sentence spectra bias subsequent phoneme categorization

Spectral differences across earlier (context) and later (target) sounds are perceptually magnified, resulting in spectral contrast effects (SCEs) that bias categorization of later sounds. Most studies added spectral peaks to context sounds in order to produce SCEs, but noise contexts with spectral notches at speech frequencies biased phoneme categorization in a complementary manner (Coady et al., 2003 JASA). We tested whether this approach generalized to speech contexts with spectral notches. On each trial, a context sentence preceded the target phoneme (Experiment 1: /ɪ/-/ɛ/; Experiment 2: /d/-/g/). Sentences were processed by notch filters that attenuated energy in the same frequency regions that, when amplified to add spectral peaks, produced SCEs (Experiment 1: 100–400/550–850 Hz, as in Stilp et al., 2015 JASA; Experiment 2: 1700–2700/2700–3700 Hz, as in Stilp & Assgari, 2017 JASA). Notch depths ranged from −5 to −20 dB in 5-dB steps. In both experiments, notch-filtered sentences biased phoneme categorization in complementary directions to SCEs, with bias magnitudes increasing at larger notch depths. Whether earlier sounds have spectral peaks or notches, speech categorization is highly sensitive to the magnitudes of spectral differences across context and target sounds.Spectral differences across earlier (context) and later (target) sounds are perceptually magnified, resulting in spectral contrast effects (SCEs) that bias categorization of later sounds. Most studies added spectral peaks to context sounds in order to produce SCEs, but noise contexts with spectral notches at speech frequencies biased phoneme categorization in a complementary manner (Coady et al., 2003 JASA). We tested whether this approach generalized to speech contexts with spectral notches. On each trial, a context sentence preceded the target phoneme (Experiment 1: /ɪ/-/ɛ/; Experiment 2: /d/-/g/). Sentences were processed by notch filters that attenuated energy in the same frequency regions that, when amplified to add spectral peaks, produced SCEs (Experiment 1: 100–400/550–850 Hz, as in Stilp et al., 2015 JASA; Experiment 2: 1700–2700/2700–3700 Hz, as in Stilp & Assgari, 2017 JASA). Notch depths ranged from −5 to −20 dB in 5-dB steps. In both experiments, notch-filtered sentences biased phoneme catego...

Short-term, not long-term, average spectra of preceding sentences bias consonant categorization

Phoneme perception is influenced by spectral properties of surrounding sounds. For example, listeners perceive /g/ (lower F3 onset) more often after sentences filtered to emphasize high-F3 frequencies, and perceive /d/ (higher F3 onset) more often after sentences filtered to emphasize low-F3 frequencies. These biases are known as spectral contrast effects (SCEs). Much of this work examined differences between long-term average spectra (LTAS) of preceding sounds and target phonemes. Stilp and Assgari (2018 ASA) revealed that spectra of the last 500 ms of precursor sentences, not the entire LTAS, predicted biases in consonant categorization. Here, the influences of Early (before the last 500 ms) versus Late (last 500 ms) portions of precursor sentences on subsequent consonant categorization were compared. Sentences emphasized different frequency regions in each temporal window (Early = low-F3 emphasis, Late = high-F3 emphasis, and vice versa) naturally or via filtering. Entire-sentence LTASes predicted that SCEs would not bias consonant categorization, but instead responses were biased by the spectrum of the Late window. This was replicated when the Early window did not emphasize either frequency region but the Late window did. Results endorse closer consideration of patterns of spectral energy over time in preceding sounds, not just their LTAS.

Spectral contrast effects produced by competing speech contexts.

The long-term spectrum of a preceding sentence can alter the perception of a following speech sound in a contrastive manner. This speech context effect contributes to our ability to extract reliable spectral characteristics of the surrounding acoustic environment and to compensate for the voice characteristics of different speakers or spectral colorations in different listening environments to maintain perceptual constancy. The extent to which such effects are mediated by low-level "automatic" processes, or require directed attention, remains unknown. This study investigated spectral context effects by measuring the effects of two competing sentences on the phoneme category boundary between /i/ and /ε/ in a following target word, while directing listeners' attention to one or the other context sentence. Spatial separation of the context sentences was achieved either by presenting them to different ears, or by presenting them to both ears but imposing an interaural time difference (ITD) between the ears. The results confirmed large context effects based on ear of presentation. Smaller effects were observed based on either ITD or attention. The results, combined with predictions from a two-stage model, suggest that ear-specific factors dominate speech context effects but that the effects can be modulated by higher-level features, such as perceived location, and by attention. (PsycINFO Database Record

Effects of spectral resolution on spectral contrast effects in cochlear-implant users.

The identity of a speech sound can be affected by the long-term spectrum of a preceding stimulus. Poor spectral resolution of cochlear implants (CIs) may affect such context effects. Here, spectral contrast effects on a phoneme category boundary were investigated in CI users and normal-hearing (NH) listeners. Surprisingly, larger contrast effects were observed in CI users than in NH listeners, even when spectral resolution in NH listeners was limited via vocoder processing. The results may reflect a different weighting of spectral cues by CI users, based on poorer spectral resolution, which in turn may enhance some spectral contrast effects.

Natural signal statistics and the timecourse of spectral context effects in consonant categorization

Speech perception is heavily influenced by surrounding sounds. When spectral properties differ between earlier (context) and later (target) sounds, this can produce spectral contrast effects (SCEs) that bias categorization of later sounds. For example, when context sounds have a low-F3 bias, listeners report more high-F3 responses to the target consonant (/d/); conversely, a high-F3 bias in context sounds produces more low-F3 responses (/g/). SCEs have been demonstrated using a variety of approaches, but most often, the context was a single sentence filtered two ways (e.g., low-F3 bias, high-F3 bias) to introduce long-term spectral properties that biased speech categorization. Here, consonant categorization (/d/-/g/) was examined following context sentences that naturally possessed desired long-term spectral properties without any filtering. Filtered sentences with equivalent spectral peaks were included as controls. For filtered context sentences, as average spectral peak magnitudes (i.e., filter gain) increased, SCE magnitudes (i.e., category boundary shifts) increased linearly. However, unfiltered context sentences showed no relationship between long-term average spectral energy and subsequent SCEs. Instead, spectral energy in the last 500 ms of unfiltered sentences predicted SCE magnitudes. Results highlight important considerations about how long-term versus short-term spectral energy in preceding sounds affects categorization of later sounds.

Trial-to-trial variability in talkers’ fundamental frequencies restrains spectral context effects in vowel categorization

Perception of a given sound is influenced by spectral properties of surrounding sounds. For example, listeners perceive /ɪ/ (low F1) more often when following sentences filtered to emphasize high-F1 frequencies, and perceive /ɛ/ (high F1) more often following sentences filtered to emphasize low-F1 frequencies. These biases in vowel categorization are known as spectral contrast effects (SCEs). When preceding sentences were spoken by acoustically similar talkers (low variability in mean f0), SCEs biased vowel categorization, but sentences spoken by acoustically different talkers (high variability in mean f0) biased vowel categorization significantly less (Assgari et al., 2016 ASA). However, it was unclear whether these effects varied due to local (trial-to-trial) or global (across entire block) variability in mean f0. Here, the same sentences were arranged to increase/decrease monotonically in mean f0 across trials (low local variability) or vary substantially from trial-to-trial (high local variability) with equal global variability. On each trial, listeners heard a sentence filtered to add a low-F1 or high-F1 spectral peak to bias categorization of a subsequent vowel (/ɪ/-/ɛ/ continuum). Sentences with low local variability in mean f0 biased vowel categorization significantly more than sentences with high local variability. Relevance to studies of talker normalization will be discussed.