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.

Consonant categorization exhibits a graded influence of surrounding spectral context.

When spectral properties differ across successive sounds, this difference is perceptually magnified, resulting in spectral contrast effects (SCEs). Recently, Stilp, Anderson, and Winn [(2015) J. Acoust. Soc. Am. 137(6), 3466-3476] revealed that SCEs are graded: more prominent spectral peaks in preceding sounds produced larger SCEs (i.e., category boundary shifts) in categorization of subsequent vowels. Here, a similar relationship between spectral context and SCEs was replicated in categorization of voiced stop consonants. By generalizing this relationship across consonants and vowels, different spectral cues, and different frequency regions, acute and graded sensitivity to spectral context appears to be pervasive in speech perception.

Talker information influences spectral contrast effects in speech categorization.

Spectral contrast effects, the perceptual magnification of spectral differences between sounds, have been widely shown to influence speech categorization. However, whether talker information alters spectral contrast effects was recently debated [Laing, Liu, Lotto, and Holt, Front. Psychol. 3, 1-9 (2012)]. Here, contributions of reliable spectral properties, between-talker and within-talker variability to spectral contrast effects in vowel categorization were investigated. Listeners heard sentences in three conditions (One Talker/One Sentence, One Talker/200 Sentences, 200 Talkers/200 Sentences) followed by a target vowel (varying from /ɪ/-/ɛ/ in F1, spoken by a single talker). Low-F1 or high-F1 frequency regions in the sentences were amplified to encourage /ɛ/ or /ɪ/ responses, respectively. When sentences contained large reliable spectral peaks (+20 dB; experiment 1), all contrast effect magnitudes were comparable. Talker information did not alter contrast effects following large spectral peaks, which were likely attributed to an external source (e.g., communication channel) rather than talkers. When sentences contained modest reliable spectral peaks (+5 dB; experiment 2), contrast effects were smaller following 200 Talkers/200 Sentences compared to single-talker conditions. Constant recalibration to new talkers reduced listeners' sensitivity to modest spectral peaks, diminishing contrast effects. Results bridge conflicting reports of whether talker information influences spectral contrast effects in speech categorization.

Contributions of natural signal statistics to spectral context effects in consonant categorization.

Speech perception, like all perception, takes place in context. Recognition of a given speech sound is influenced by the acoustic properties of surrounding sounds. When the spectral composition of earlier (context) sounds (e.g., a sentence with more energy at lower third formant [F3] frequencies) differs from that of a later (target) sound (e.g., consonant with intermediate F3 onset frequency), the auditory system magnifies this difference, biasing target categorization (e.g., towards higher-F3-onset /d/). Historically, these studies used filters to force context stimuli to possess certain spectral compositions. Recently, these effects were produced using unfiltered context sounds that already possessed the desired spectral compositions (Stilp & Assgari, 2019, Attention, Perception, & Psychophysics, 81, 2037-2052). Here, this natural signal statistics approach is extended to consonant categorization (/g/-/d/). Context sentences were either unfiltered (already possessing the desired spectral composition) or filtered (to imbue specific spectral characteristics). Long-term spectral characteristics of unfiltered contexts were poor predictors of shifts in consonant categorization, but short-term characteristics (last 475 ms) were excellent predictors. This diverges from vowel data, where long-term and shorter-term intervals (last 1,000 ms) were equally strong predictors. Thus, time scale plays a critical role in how listeners attune to signal statistics in the acoustic environment.

Natural speech statistics shift phoneme categorization.

All perception takes place in context. Recognition of a given speech sound is influenced by the acoustic properties of surrounding sounds. When the spectral composition of earlier (context) sounds (e.g., more energy at lower first formant [F1] frequencies) differs from that of a later (target) sound (e.g., vowel with intermediate F1), the auditory system magnifies this difference, biasing target categorization (e.g., towards higher-F1 /ɛ/). Historically, these studies used filters to force context sounds to possess desired spectral compositions. This approach is agnostic to the natural signal statistics of speech (inherent spectral compositions without any additional manipulations). The auditory system is thought to be attuned to such stimulus statistics, but this has gone untested. Here, vowel categorization was measured following unfiltered (already possessing the desired spectral composition) or filtered sentences (to match spectral characteristics of unfiltered sentences). Vowel categorization was biased in both cases, with larger biases as the spectral prominences in context sentences increased. This confirms sensitivity to natural signal statistics, extending spectral context effects in speech perception to more naturalistic listening conditions. Importantly, categorization biases were smaller and more variable following unfiltered sentences, raising important questions about how faithfully experiments using filtered contexts model everyday speech perception.

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.

Perceptual sensitivity to spectral properties of earlier sounds during speech 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 perception of later sounds. For example, when context sounds have more energy in low-F1 frequency regions, listeners report more high-F1 responses to a target vowel, and vice versa. SCEs have been reported using various approaches for a wide range of stimuli, but most often, large spectral peaks were added to the context to bias speech categorization. This obscures the lower limit of perceptual sensitivity to spectral properties of earlier sounds, i.e., when SCEs begin to bias speech categorization. Listeners categorized vowels (/ɪ/-/ɛ/, Experiment 1) or consonants (/d/-/g/, Experiment 2) following a context sentence with little spectral amplification (+1 to +4 dB) in frequency regions known to produce SCEs. In both experiments, +3 and +4 dB amplification in key frequency regions of the context produced SCEs, but lesser amplification was insufficient to bias performance. This establishes a lower limit of perceptual sensitivity where spectral differences across sounds can bias subsequent speech categorization. These results are consistent with proposed adaptation-based mechanisms that potentially underlie SCEs in auditory perception. SIGNIFICANCE STATEMENT: Recent sounds can change what speech sounds we hear later. This can occur when the average frequency composition of earlier sounds differs from that of later sounds, biasing how they are perceived. These "spectral contrast effects" are widely observed when sounds' frequency compositions differ substantially. We reveal the lower limit of these effects, as +3 dB amplification of key frequency regions in earlier sounds was enough to bias categorization of the following vowel or consonant sound. Speech categorization being biased by very small spectral differences across sounds suggests that spectral contrast effects occur frequently in everyday speech perception.

Speech perception adjusts to stable spectrotemporal properties of the listening environment.

When perceiving speech, listeners compensate for reverberation and stable spectral peaks in the speech signal. Despite natural listening conditions usually adding both reverberation and spectral coloration, these processes have only been studied separately. Reverberation smears spectral peaks across time, which is predicted to increase listeners' compensation for these peaks. This prediction was tested using sentences presented with or without a simulated reverberant sound field. All sentences had a stable spectral peak (added by amplifying frequencies matching the second formant frequency [F2] in the target vowel) before a test vowel varying from /i/ to /u/ in F2 and spectral envelope (tilt). In Experiment 1, listeners demonstrated increased compensation (larger decrease in F2 weights and larger increase in spectral tilt weights for identifying the target vowel) in reverberant speech than in nonreverberant speech. In Experiment 2, increased compensation was shown not to be due to reverberation tails. In Experiment 3, adding a pure tone to nonreverberant speech at the target vowel's F2 frequency increased compensation, revealing that these effects are not specific to reverberation. Results suggest that perceptual adjustment to stable spectral peaks in the listening environment is not affected by their source or cause.