Preferences for Very Low and Very High Voice Pitch in Humans

Abstract

Manipulations of voice pitch have been shown to alter attractiveness ratings, but whether preferences extend to very low or very high voice pitch is unknown. Here, we manipulated voice pitch in averaged men's and women's voices by 2 Hz intervals to create a range of male and female voices speaking monopthong vowel sounds and spanning a range of frequencies from normal to very low and very high pitch. With these voices, we used the method of constant stimuli to measure preferences for voice. Nineteen university students (ages: 20–25) participated in three experiments. On average, men preferred high-pitched women's voices to low-pitched women's voices across all frequencies tested. On average, women preferred men's voices lowered in pitch, but did not prefer very low men's voices. The results of this study may reflect selection pressures for men's and women's voices, and shed light on a perceptual link between voice pitch and vocal attractiveness.

About the Authors:

Daniel E. Re

Affiliation: Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, Ontario, Canada

Jillian J. M. O'Connor

Affiliation: Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, Ontario, Canada

Patrick J. Bennett

Affiliation: Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, Ontario, Canada

David R. Feinberg

* E-mail: [email protected]

Affiliation: Department of Psychology, Neuroscience and Behaviour, McMaster University, Hamilton, Ontario, Canada

Introduction

Preferences for stimuli that exaggerate sexually-selected features are found throughout the animal kingdom. For example, female sticklebacks prefer artificial mates that are larger than naturally occurring males [1], male silver-washed fritillary butterflies are attracted to abnormally rapid movement of females' wings [2], female canaries are drawn to songs with synthetically enhanced syllable rates [3], and female stalk-eyed flies prefer males with unnaturally long eye-stalks [4].

One trait in humans that appears to have undergone intense sexual selection is the average fundamental frequency of the voice [5]. The perception of fundamental frequency and corresponding harmonics is commonly known as voice pitch. While voice pitch reflects allometric scaling in several primate species [6], [7], humans appear to be unique among primates in that sexual dimorphism of adult voice pitch is well beyond what may be explained by height alone [8], [9], [10]. The human larynx is made of cartilage and muscle that are rich in androgen receptors and grow rapidly during puberty [11], [12]. Men's vocal cords lengthen and thicken much more so than women's, resulting in the adult male voice pitch being on average half the frequency of adult female voice pitch [11]. Historical records of male singers that were castrated before puberty indicate that voice pitch does not reach adult male levels in the absence of testicular hormones at puberty [13]. Similarly, case studies of male-to-female transsexuals indicate that although women may have different quantities and sensitivities of androgen receptors on their vocal cords, administering exogenous testosterone to women does lead to a drop in voice pitch [14]. Furthermore, after menopause, the pitch of many women's voices drops, most likely due to a decrease in estrogen production and an increase in testosterone production [15], [16]. Thus, voice pitch is indicative of laryngeal development, and is dependent on pubertal and fluctuating levels of sex hormones [11], [16].

Several empirical studies have found that in general, women prefer lower-pitched men's voices to higher-pitched men's voices [17], [18], [19], [20], [21], [22], [23]. Men with lower-pitched voices also have higher reproductive success than men with higher-pitched voices [24]. Conversely, men typically prefer high-pitched women's voices over low-pitched women's voices [25], [26], [27]. High-pitched women's voices are perceived as feminine and youthful [25], [27] and flirtatious [28], and increase the perceived likelihood of sexual infidelity [29]. Furthermore, women tend to raise their voice pitch when presented with an attractive man's face and asked to leave a phone message for him [30].

In general, men prefer high-pitched women's voices whereas women prefer low-pitched men's voices, however two studies obtained opposing results when analyzing men's preferences at the upper limit of the natural frequency range of women's voices [27], [31]. Specifically, one study found that men prefer these very high-pitched voices [27] whereas the other study shows that men did not prefer these voices [31]. Therefore it is important to further investigate whether men and women prefer very high and very low voice pitch, respectively. Determining if people exhibit preferences for voice pitch beyond that fall below or above (very low or very high) what is normally produced in a population may shed light on whether preferences for men's and women's voice pitch are directional or stabilizing. Preferences for very low pitch in men's voices and/or very high pitch in women's voices may suggest directional preferences [32], but a lack of such preferences for such extreme voice pitches may indicate stabilizing preferences.

The ability to discriminate vocal frequencies also may constrain men's preferences for high-pitched women's voices. The relationship between physical and perceived frequencies is logarithmic such that as physical frequency increases, the ability to hear the difference between frequencies diminish, thus making it more difficult to discriminate high frequency voices than low frequency voices [33]. Men's preferences for women's voices may therefore be limited by two non-mutually exclusive adaptive mechanisms to negate disparities in physical and perceived frequencies and avoid poor mate-choice decisions: (1) a cut-off point where men are averse to very high-pitched women's voices, ensuring formant frequency discrimination is not limited by voice pitch; (2) ensuring the difference in pitch required to change attractiveness ratings is tied to logarithmic pitch perception. Here we would expect larger just-noticeable differences (JNDs) in attractiveness ratings than for pitch discrimination to minimize error in potentially costly mate-choice decisions.

The current experiments tested for perceptual boundaries on preferences for voice pitch, and examined whether preferences for voice pitch are directional or stabilizing. We manipulated men and women's voices in 2 Hz intervals of voice pitch from above and below the normal range of men and women's voices and presented each voice to opposite-sex participants to measure voice preferences.

Methods

Protocols for this study were approved by the McMaster University Research Ethics Board. All participants gave written informed consent prior to participating.

Stimuli

To create voices representative of a given population, we created an initial male and female voice speaking the English monopthong vowel sounds: ‘eh’ as in ‘bet’, ‘ee’ as in ‘see’, ‘ah’ as in ‘father’, ‘oh’ as in ‘note’, and ‘oo’ as in ‘boot’. Such stimuli have been used in many studies on voice perception [17], [22], [27], [34], [35]. Initial voices were created from an average of 32 male (mean: 109.99 Hz, SD: 3.18 Hz, range: 86–152 Hz) and 32 female voices (mean: 210.81 Hz, SD: 20.67 Hz, range: 143–285 Hz), separately, using STRAIGHT [36]. Briefly, this procedure entails pitch extraction, and demarcating key spectral features (e.g., formant frequencies and vowel onset and offset) on spectrograms of the sound (Figure 1). These features are then aligned in time, and then fundamental frequency and harmonics, amplitude, time, and formant frequencies are then averaged separately, and voices reconstructed. This method has been used successfully in other studies of voice processing [37]. The averaging process averaged voices in pairs, iteratively, until one base voice of each sex were created from an average of 32 voices. The final pitches of the averaged voices were 110 Hz for the male voice and 211 Hz for the female voice. Spectrograms of the average male and female voice used in this study are shown in Figure 1.

[Figure omitted. See PDF.]

Figure 1. Spectrograms of the average female (left panel) and male voice (right panel) for the five vowel sound stimuli.

Spectrograms plot time on the X axis, frequency on the Y axis, and amplitude is represented by shading.

https://doi.org/10.1371/journal.pone.0032719.g001

Next, we manipulated voice pitch using the Pitch-Synchronous Overlap Add (PSOLA) algorithm [38] in Praat acoustic phonetics software [39]. The initial voices were manipulated in 2 Hz steps using the PSOLA method. The PSOLA method selectively manipulates mean fundamental frequency and corresponding harmonics independent of time and formant frequencies, and has been used successfully in many studies on voice preferences and other mate-choice relevant contexts in humans [17], [21], [22], [27], [40], [41], and other mammalian species [42], [43]. Although voice pitch was manipulated, formant frequencies were retained, and previous research has demonstrated that such manipulations create voices that still sound “adult-like” [35]. The pitch range for men's voices was 60–180 Hz, and the pitch range of women's voices was 160–300 Hz. These pitch ranges extend well below the 32 men's voices and above the 32 women's voices used in creating the initial averaged voices. Praat's pitch parameters were set at a minimum 50 Hz and maximum 300 Hz for men's voices, and a minimum 100 Hz and maximum 600 Hz for women's voices. Window length was determined automatically by Praat.

Participants and procedures

Ten men (mean age: 21.80, SD: 1.45) and nine women (mean age: 22.05, SD: 1.58) participated in the study. All were university students with normal hearing. All participants reported English as their first language, and no participant reported any musical training. Participants rated voices in a 2-alternative forced-choice paradigm: on each trial, two voices were presented, one after the other. Participants were free to replay the voices as desired. Voice trials were presented using the method of constant stimuli [44]. In this method, each voice pitch was compared to every other pitch in random order. The method of constant stimuli was chosen to avoid auditory adaptation to stimuli which may have affected JNDs. Furthermore, extensive sampling of the pitch dimension allowed for an in-depth analysis of possible perceptual constraints on preferences for voice pitch. Extensive sampling of few participants is common practice in auditory psychophysics [45], [46], [47], [48], [49], [50], [51].

Men listened to all possible pairs of women's voices, and women listened to all possible pairs of men's voices. Catch trials (i.e., no difference in pitch) at each pitch interval were included. Men listened to 51 blocks of 50 voice pairs and 1 block of 6 voice pairs, while women listened to 37 blocks of 50 voice pairs and 1 block of 42 voice pairs. Each block of 50 voice pairs took approximately 15 minutes to complete, and participants completed a maximum of eight blocks per day. Each task took several weeks to complete. The frequencies of all voices were randomized within and between blocks. In all, males listened to 2556 voice pairs, and females listened to 1892 voice pairs.

The study was divided into three tasks. The first task was a simple pitch discrimination task. Four men and four women were asked to pick the voice with the higher pitch [47]. Several previous studies have assessed JNDs in pitch for vowel sounds [45], [46], [52], [53].

The second task was created to determine JNDs in vocal attractiveness based on pitch manipulations. Four men and four women listened to all the voice trials and were asked to pick the voice they thought was more attractive. Two men and three women who completed the pitch discrimination task also completed the voice attractiveness task. As tasks were performed months apart, it is unlikely the voice attractiveness task affected performance on the pitch discrimination task.

The third task assessed JNDs in voice pitch for perception of vocal dimorphism (masculinity or femininity). Four men and four women participated in the third experiment. Men were presented with pairs of women's voices and were asked to choose the voice they thought was more feminine (as in [27]). Women were presented with pairs of men's voices and were asked to choose which voice they thought was more masculine.

Results

Pitch discrimination task

Psychometric functions were created for each participant by plotting the proportion of correct responses as a function of the Weber fraction (the difference in pitch between the two voices in a trial divided by the lower pitch value). Regression was used to estimate the best-fitting logit or probit function to each participant's data. Catch trials were not included in the psychometric functions, but were used as an index of side bias that was included as a predictor in the regression model. The JND was defined as the Weber fraction that produced correct responses on 75% of trials [54]. Individual JNDs for each participant can be seen in Table 1. The regression model provided good fit to the data, and accounted for a significant amount of variance for each participant (χ2>158.0, p<0.01 in all cases). We failed to find a significant difference between men's and women's pitch discrimination thresholds (independent-sample t-test: t(6) = 0.54, p = 0.61, Cohen's d = 0.38). Thus, we collapsed our analysis across sexes. The average JND for pitch discrimination across the eight participants was 4.1% (SD: 1.9%). See Table 1 for all averaged JNDs.

[Figure omitted. See PDF.]

Table 1. Individual and average just-noticeable differences for men and women in all three tasks.

https://doi.org/10.1371/journal.pone.0032719.t001

Vocal attractiveness task

Psychometric functions were created for each participant in the vocal attractiveness task by plotting the proportion of trials a subject preferred the higher-pitched voice as a function of the Weber fraction, and fitting logistic or probit functions to the data. Just-noticeable differences were determined for each participant. Men's and women's JNDs were analyzed separately. For men rating women's voices, the JND was defined as the Weber fraction at which participants rated the higher-pitched voice as more attractive on 75% of trials [54]. Regression analyses revealed a significant association between attractiveness and the Weber fraction for each male participant (χ2>155.8, p<0.01 in all cases). The JNDs of the four male participants were averaged to determine an average JND of 18.2% (SD: 8.6%). Preferences for high-pitched women's voices increased monotonically with Weber fraction, and were maintained across the entire range of presented frequencies (Figure 2).

[Figure omitted. See PDF.]

Figure 2. Men's vocal preferences as a function of lower frequency (Hz) and the difference between two voices (Hz) in a voice trial.

Men preferred higher-pitched voices across the range of women's frequencies where the stimuli difference is above the JND in attractiveness of 18.2%. Preferences were averaged across all four male participants.

https://doi.org/10.1371/journal.pone.0032719.g002

To test whether there were limits to how high or low voice pitch could be manipulated and still sound attractive, we created linear and quadratic models of preference strength as a function of Weber fraction and lower frequency. We then assessed the goodness of fits of the linear and quadratic models. If there are directional preferences for high-pitched women's voices, preference strength would be best fit by a linear model. If there are stabilizing preferences, preference strength would be best represented by a “U” shaped quadratic model in which the apex of the “U” occurs where preference strength is weakest. Both the linear (F(1, 2484) = 785.7, p<0.01) and the quadratic (F(2, 2484) = 393.0, p<0.01) models were significant. We determined which model provided a better fit to the data by using Akaike's Information Criterion [55], which is sensitive to residual error as well as the number of parameters used in each model. The information criterion test revealed an Akaike's Information Criteria of 2 (quadratic-linear), giving a 73% probability that the linear model was the better fit. The linear model was therefore 2.7 times more likely to produce a better fit than the quadratic model. Thus, stabilizing preferences are less likely than directional preferences given the range of frequencies tested here.

For women rating men's voices, the JND was defined as the Weber fraction at which participants rated the lower-pitched voice as more attractive 75% of the time [54]. Regression analyses revealed a significant association between attractiveness and the Weber fraction for each participant (χ2>30.7, p<0.01 in all cases). However, women's preferences for the lower-pitched men's voices were not a monotonic function of frequency. Instead, women preferred low-pitched voices on trials that contained a lower frequency voice that was greater than 96 Hz, but preferred the higher-pitched voice on trials in which the lower voice frequency was less than 96 Hz (Figure 3). Thus, women did not prefer low-pitched men's voices on trials in which the lower frequency was extremely low.

[Figure omitted. See PDF.]

Figure 3. Women's vocal preferences as a function of lower frequency (Hz) and the difference in between two voices (Hz) in a voice trial.

Women preferred lower-pitched voices in trials where the lower-pitched voice was above ∼96 Hz, however, they preferred the higher-pitched voice in trials where the lower-pitched voice fell below ∼96 Hz. Preferences were averaged across all four female participants.

https://doi.org/10.1371/journal.pone.0032719.g003

Again, both linear and quadratic models of preference strength were produced to empirically test whether preferences were directional or stabilizing. Stabilizing preferences would be best represented by a “U” shaped quadratic model where the apex of the “U” shape occurs at the inversion in preferences. Directional preferences would best be represented by a linear model. The quadratic model was significant (F(2, 1823) = 19.2, p<0.01), however the linear model was not significant (F(1, 1823) = 1.44, p = 0.23). We tested which model better fit the data via Akaike's Information Criterion. The information criterion test revealed an Akaike's Information Criteria of −35.6 (quadratic-linear), giving a 99.99% probability that the quadratic model was the better fit. The quadratic model was therefore 54 027 298 times more likely to produce a better fit than the linear model. Thus, the data strongly suggest that women's preferences for voice pitch are stabilizing, such that women prefer voices raised in pitch to very low pitch.

Due to the fact that preferences were not a monotonic function of frequency, JNDs for women's ratings of men's vocal attractiveness were calculated using only responses collected with voice frequencies ranging from 110 Hz to 180 Hz. Setting the lowest pitch to 110 Hz, rather than 96 Hz, ensured that any residual preferences for the higher-pitched voice was excluded. The shortened pitch range still contained 666 trials, which is sufficient to create an accurate psychometric function. Within this range of frequencies, preference for the lower-pitched voice was related monotonically and significantly to the Weber fraction for each participant (χ2>30.65, p<0.01 in all cases), and the average JND for women rating men's voices for attractiveness was 8.8% (SD: 2.7%). The difference between JNDs for men's and women's ratings of attractiveness approached significance (independent-sample t-test: t(6) = 2.05, p = 0.08, Cohen's d = 1.45).

Vocal dimorphism task

For men rating women's voices, the JND was defined as the Weber fraction at which participants rated the higher-pitched voice as more feminine on 75% of trials [54]. The regression analyses revealed a significant association between perceived dimorphism and the Weber fraction for all participants (χ2>125.7, p<0.01 in all cases). The average JND for men rating women's voices for femininity was 5.6% (SD: 4.9%).

For women rating men's voices, the JND was defined as the Weber fraction at which participants rated the lower-pitched voice as more masculine on 75% of trials [54]. The regression analyses revealed a significant association between perceived dimorphism and the Weber fraction for all participants (χ2>152.0, p<0.01 in all cases). The average JND for women rating men's voices for masculinity was 6.5% (SD: 4.3%).

Comparison of JNDs across tasks

The JNDs for pitch discrimination, vocal attractiveness, and vocal dimorphism were compared. The JNDs for pitch discrimination were collapsed across sex (8 JNDs), as there were no significant differences in men's and women's pitch discrimination. The JNDs for vocal attractiveness and vocal dimorphism were kept within-sex (4 JNDs).

A Welch independent sample t-test was used to assess differences between pitch discrimination and ratings of vocal attractiveness. A Welch t-test was used as the groups did not satisfy the assumption of equal variance. The t-test revealed significant differences between JNDs for pitch discrimination and men's ratings of attractiveness (t(3.2) = 3.20, p<0.05, Cohen's d = 2.24). An independent samples t-test revealed a significant difference between pitch discrimination and women's ratings of vocal attractiveness (t(10) = 3.45, p<0.01, Cohen's d = 1.93).

Independent-sample t-tests failed to find significant differences between the pitch discrimination and men's ratings of vocal femininity (t(10) = 0.73, p = 0.48, Cohen's d = 0.38) or between pitch discrimination and women's ratings of vocal masculinity (t(10) = 1.36, p = 0.20, Cohen's d = 0.72).

An independent-sample t-test revealed a significant difference between men's ratings of vocal attractiveness and men's ratings of vocal femininity (t(6) = 2.54, p = 0.04, Cohen's d = 2.12). An independent-sample t-test did not reveal a significant difference between women's ratings of vocal attractiveness and women's ratings of vocal masculinity (t(6) = −0.90, p = 0.40, Cohen's d = 0.64).

Discussion

We found that men preferred high-pitched women's voices to low-pitched women's voices, even when voice pitch was above the normal speaking range, and our analyses suggest that men's preferences for high voice pitch in women may contribute to directional selection on women's voice pitch. These data also support previous findings that men prefer high-pitched women's voices to low-pitched women's voices [26], [53], [56], [57], [58], [59], [60]. Such preferences for very high voice pitch among women may be adaptive as voice pitch is indicative of potential reproductive health [61] and youth. Some women's voices may naturally fall below the 160 Hz minimum we used in the current study, however the higher-pitched voice was preferred in all trials presented, and it is unlikely preferences would invert below the pitch range studied. We used women's voices with pitches as high as 300 Hz; higher than the voice pitch range among women in our sample (143–285 Hz) however it is possible that men do not prefer voice pitch higher than the frequencies tested here. Indeed, above 300 Hz, there exists the possibility that the fundamental frequency of manipulated voices could be higher than the first formant frequency, creating speech-like sounds that are physically impossible for humans to make. That did not occur in the stimuli used in our experiments.

We found that, on average, women preferred a lower pitched voice over a higher pitched voice except when the lower frequency was below ∼96 Hz, in which case women tended to prefer the higher pitched voice. While a natural pitch of 96 Hz or lower can be found in some men, it is rare and falls outside the standard deviation of the frequencies used to create stimuli in the current experiment. Thus, women prefer low pitch in men's voices, but not very low pitch. Such preferences may contribute to stabilizing selection pressure for low pitch in men's voices [32]. One possible mechanism underlying this constraint may be the anatomical properties of the vocal cords themselves. Extremely low voice pitch may be indicative of pathology, or laryngeal damage caused by smoking [62], [63]. Such voice pitch may also be indicative of overspending of resources on producing a large larynx, such as in hyperpituitarism [64]. Voices below 70 Hz may even sound unnaturally “pulsed” rather than modal [11]. Furthermore, the perception of vowel sounds is attenuated when fundamental frequency is too low [47], and rich semantic and emotional information given by intonation in speech and singing may be difficult to perceive at such low frequencies [11].

The female participants in the current study were all university students in their early twenties. Previous research has demonstrated that women's voice preferences are developed in adolescence [20], however it is possible that preferences change with age. Indeed, men's voice pitch does change throughout adult development [65], [66], and preferences may change as a form of age-related assortative mating (as has been found in other mammals, [67]). Age-related changes in men's voices are relatively minimal (∼6–8 Hz, [65], [66]), however, and the preference limit on low-pitched men's voices was around 96 Hz, well below average male voice pitch and beyond changes in pitch associated with age. Thus, it is unlikely that participant age affected the limitation on preferences for low-pitched men's voices found here.

We found in both sexes that preferences for voice pitch varied logarithmically with respect to physical pitch, indicating a perceptual link between preferences for voice pitch and physical frequency of the voice itself. Feinberg et al. [27] found that raising and lowering the pitch of female voices by 20 Hz had a stronger effect on voices that were low in pitch before being manipulated than on voices that were average-pitched or high-pitched before manipulation. These effects, however, were not found for femininity ratings. Thus, it was unknown whether the diminishing effect of changes in voice pitch on attractiveness as the lower voice pitch increased was due to the Weber-Fechner Law, or a maximum frequency that men find attractive in women's voices. The research reported here suggests preferences for voice pitch are influenced by the Weber-Fechner Law.

Just noticeable differences in preferences for voice-pitch were significantly higher than both JNDs for masculinity/femininity ratings and pitch discrimination. This may be due to the difference in the degree of neural processing involved in the pitch discrimination and vocal attractiveness tasks. Pitch discrimination requires a straightforward decision on pitch intensity [68], [69] and involves voice-selective neural systems [70]. Judgments of attractiveness likely require involvement from neural reward centers [71] and neural areas involved in processing speaker identity [72]. The JNDs in vocal dimorphism, however, were not significantly different from those for pitch discrimination. Thus, the differences in JNDs between tasks cannot be attributed to pitch discrimination having an objectively correct answer while social attributions do not. The perceptual link between pitch and attractiveness may be less tightly coupled because vocal attractiveness is based on several vocal parameters besides pitch, including formant frequencies [17], [23], [53], [73], intonation [74], and word content [23], [40]. Regardless of the proximate mechanism, poor mate-choice decisions can be costly for both men and women [75], and thus it may be functionally adaptive for JNDs in attractiveness to be relatively larger than JNDs for pitch discrimination.

Several studies have assessed JNDs in pitch for spoken sounds and have found discrimination thresholds ranging from 1–2% [45], [46], [51] for synthetic vowel sounds to 6% for spoken vowel sounds [53] and 7% for naturalistic sentences [73]. Pisanksi and Rendall [53] described how JNDs may be larger for vocalized vowel sounds than synthetic vowel sounds due to increased spectral variation in human vocalizations. Another reason why our JNDs in pitch discrimination are higher than previous studies is that participants in our study made assessments after hearing an entire series of vowels, rather than making assessments after individual vowels as in other studies [45], [46], [51]. Indeed, JNDs for pitch discrimination are much higher for sentences than individual vowels [73], suggesting that the added pitch variation over a longer utterance can make it harder to discriminate average pitch between utterances.

The current study used digitally averaged voices. Previous research has demonstrated that averaged voices can be perceived as more attractive than component voices, due to reducing vocal aperiodicties that can be present in any individual voice [76]. Thus, the initial averaged voices may be more attractive than their component voices. All stimuli in the current study were products of averaged voices, which were then compared against each other to determine preference limitations and JNDs. Since the current experiments pitted averaged voices against other averaged voices, we see no reason why relative pitch preferences and JNDs should not be generalizable, though it is possible results using natural voices may vary. It is also important to note that formant frequencies for the averaged voices were retained after digital pitch manipulations. Formant frequencies interact with pitch to affect judgments of size [47] and attractiveness [77], thus manipulating formants along with pitch may affect the current results.

In summary, our results demonstrate that men prefer high-pitched women's voices at very high frequencies, while women do not prefer low-pitched men's voices at very low frequencies. This may reflect different selection pressures acting on voice pitch in men and women. Just-noticeable differences in perceived vocal attractiveness are significantly greater than those needed to discriminate pitch, which in turn were not significantly different from those needed to alter perceived vocal masculinity and femininity. If our ancestors also exhibited these perceptual constraints on the relationship between voice pitch and vocal attractiveness, this may have helped shape the evolution of sex differences in voice pitch.

Author Contributions

Conceived and designed the experiments: DR PB DF. Performed the experiments: DR DF. Analyzed the data: DR JO PB DF. Contributed reagents/materials/analysis tools: DR JO DF. Wrote the paper: DR JO PB DF.

Citation: Re DE, O'Connor JJM, Bennett PJ, Feinberg DR (2012) Preferences for Very Low and Very High Voice Pitch in Humans. PLoS ONE7(3): e32719. https://doi.org/10.1371/journal.pone.0032719

References

1. Rowland WJ (1989) Mate Choice and the Supernormality Effect in Female Sticklebacks (Gasterosteus-Aculeatus). Behav Ecol Sociobiol 24: 433–438.WJ Rowland1989Mate Choice and the Supernormality Effect in Female Sticklebacks (Gasterosteus-Aculeatus).Behav Ecol Sociobiol24433438

2. Magnus DBE (1958) Experimental analysis of some “overoptimal” sign-stimuli in the mating-behaviour of the fritillary butterfly Argynnis paphia L. (Lepidoptera: Nymphalidae). pp. 405–418.DBE Magnus1958Experimental analysis of some “overoptimal” sign-stimuli in the mating-behaviour of the fritillary butterfly Argynnis paphia L. (Lepidoptera: Nymphalidae).405418Proceedings of the Tenth International Congress of Entomology. Proceedings of the Tenth International Congress of Entomology.

3. Draganoiu TI, Nagle L, Kreutzer M (2002) Directional female preference for an exaggerated male trait in canary (Serinus canaria) song. P R Soc B269: 2525–2531.TI DraganoiuL. NagleM. Kreutzer2002Directional female preference for an exaggerated male trait in canary (Serinus canaria) song.P R SocB26925252531

4. Burkhardt D, Delamotte I (1988) Big Antlers Are Favored - Female Choice in Stalk-Eyed Flies (Diptera, Insecta), Field Collected Harems and Laboratory Experiments. J Comp Physiol A 162: 649–652.D. BurkhardtI. Delamotte1988Big Antlers Are Favored - Female Choice in Stalk-Eyed Flies (Diptera, Insecta), Field Collected Harems and Laboratory Experiments.J Comp Physiol A162649652

5. Feinberg D (2008) Are human faces and voices ornaments signaling common underlying cues to mate value? Evolutionary Anthropology 17: 112–118.D. Feinberg2008Are human faces and voices ornaments signaling common underlying cues to mate value?Evolutionary Anthropology17112118

6. Rendall D, Kollias S, Ney C, Lloyd P (2005) Pitch (F-0) and formant profiles of human vowels and vowel-like baboon grunts: The role of vocalizer body size and voice-acoustic allometry. J Acoust Soc Am 117: 944–955.D. RendallS. KolliasC. NeyP. Lloyd2005Pitch (F-0) and formant profiles of human vowels and vowel-like baboon grunts: The role of vocalizer body size and voice-acoustic allometry.J Acoust Soc Am117944955

7. Pfefferle D, Fischer J (2006) Sounds and size: identification of acoustic variables that reflect body size in hamadryas baboons, Papio hamadryas. Anim Behav 72: 43–51.D. PfefferleJ. Fischer2006Sounds and size: identification of acoustic variables that reflect body size in hamadryas baboons, Papio hamadryas.Anim Behav724351

8. Evans S, Neave N, Wakelin D (2006) Relationships between vocal characteristics and body size and shape in human males: An evolutionary explanation for a deep male voice. Biol Psychol 72: 160–163.S. EvansN. NeaveD. Wakelin2006Relationships between vocal characteristics and body size and shape in human males: An evolutionary explanation for a deep male voice.Biol Psychol72160163

9. Lass NJ, Brown WS (1978) Correlational Study of Speakers Heights, Weights, Body-Surface Areas, and Speaking Fundamental Frequencies. J Acoust Soc Am 63: 1218–1220.NJ LassWS Brown1978Correlational Study of Speakers Heights, Weights, Body-Surface Areas, and Speaking Fundamental Frequencies.J Acoust Soc Am6312181220

10. Kunzel HJ (1989) How Well Does Average Fundamental-Frequency Correlate with Speaker Height and Weight. Phonetica 46: 117–125.HJ Kunzel1989How Well Does Average Fundamental-Frequency Correlate with Speaker Height and Weight.Phonetica46117125

11. Titze IR (1994) Principles of vocal production. Englewood Cliffs, NJ: Prentice Hall. IR Titze1994Principles of vocal productionEnglewood Cliffs, NJPrentice Hall

12. Newman SR, Butler J, Hammond EH, Gray SD (2000) Preliminary report on hormone receptors in the human vocal fold. J Voice 14: 72–81.SR NewmanJ. ButlerEH HammondSD Gray2000Preliminary report on hormone receptors in the human vocal fold.J Voice147281

13. Jenkins JS (1998) The voice of the castrato. Lancet 351: 1877–1880.JS Jenkins1998The voice of the castrato.Lancet35118771880

14. Damrose EJ (2009) Quantifying the impact of androgen therapy on the female larynx. Auris Nasus Larynx 36: 110–112.EJ Damrose2009Quantifying the impact of androgen therapy on the female larynx.Auris Nasus Larynx36110112

15. Russell A, Penny L, Pemberton C (1995) Speaking Fundamental-Frequency Changes over Time in Women - a Longitudinal-Study. J Speech Hear Res 38: 101–109.A. RussellL. PennyC. Pemberton1995Speaking Fundamental-Frequency Changes over Time in Women - a Longitudinal-Study.J Speech Hear Res38101109

16. Abitbol J, Abitbol P, Abitbol B (1999) Sex hormones and the female voice. J Voice 13: 424–446.J. AbitbolP. AbitbolB. Abitbol1999Sex hormones and the female voice.J Voice13424446

17. Feinberg DR, Jones BC, Little AC, Burt DM, Perrett DI (2005) Manipulations of fundamental and formant frequencies influence the attractiveness of human male voices. Anim Behav 69: 561–568.DR FeinbergBC JonesAC LittleDM BurtDI Perrett2005Manipulations of fundamental and formant frequencies influence the attractiveness of human male voices.Anim Behav69561568

18. Vukovic J, Jones BC, DeBruine L, Feinberg DR, Smith FG, et al. (2010) Women's own voice pitch predicts their preferences for masculinity in men's voices. Behav Ecol 21: 767–772.J. VukovicBC JonesL. DeBruineDR FeinbergFG Smith2010Women's own voice pitch predicts their preferences for masculinity in men's voices.Behav Ecol21767772

19. Collins SA (2000) Men's voices and women's choices. Anim Behav 60: 773–780.SA Collins2000Men's voices and women's choices.Anim Behav60773780

20. Saxton TK, Caryl PG, Roberts SC (2006) Vocal and facial attractiveness judgments of children, adolescents and adults: The ontogeny of mate choice. Ethology 112: 1179–1185.TK SaxtonPG CarylSC Roberts2006Vocal and facial attractiveness judgments of children, adolescents and adults: The ontogeny of mate choice.Ethology11211791185

21. Feinberg DR, Jones BC, Law-Smith MJ, Moore FR, DeBruine LM, et al. (2006) Menstrual cycle, trait estrogen level, and masculinity preferences in the human voice. Horm Behav 49: 215–222.DR FeinbergBC JonesMJ Law-SmithFR MooreLM DeBruine2006Menstrual cycle, trait estrogen level, and masculinity preferences in the human voice.Horm Behav49215222

22. Little AC, Saxton TK, Roberts SC, Jones BC, DeBruine LM, et al. (2010) Women's preferences for masculinity in male faces are highest during reproductive age range and lower around puberty and post-menopause. Psychoneuroendocrino 35: 912–920.AC LittleTK SaxtonSC RobertsBC JonesLM DeBruine2010Women's preferences for masculinity in male faces are highest during reproductive age range and lower around puberty and post-menopause.Psychoneuroendocrino35912920

23. Hodges-Simeon CR, Gaulin SJC, Puts DA (2010) Different Vocal Parameters Predict Perceptions of Dominance and Attractiveness. Hum Nature-Int Bios 21: 406–427.CR Hodges-SimeonSJC GaulinDA Puts2010Different Vocal Parameters Predict Perceptions of Dominance and Attractiveness.Hum Nature-Int Bios21406427

24. Apicella CL, Feinberg DR, Marlowe FW (2007) Voice pitch predicts reproductive success in male hunter-gatherers. Biol Letters 3: 682–684.CL ApicellaDR FeinbergFW Marlowe2007Voice pitch predicts reproductive success in male hunter-gatherers.Biol Letters3682684

25. Collins SA, Missing C (2003) Vocal and visual attractiveness are related in women. Anim Behav 65: 997–1004.SA CollinsC. Missing2003Vocal and visual attractiveness are related in women.Anim Behav659971004

26. Fraccaro PJ, Feinberg DR, DeBruine LM, Little AC, Watkins CD, et al. (2010) Correlated Male Preferences for Femininity in Female Faces and Voices. Evolutionary Psychology 8: 447–461.PJ FraccaroDR FeinbergLM DeBruineAC LittleCD Watkins2010Correlated Male Preferences for Femininity in Female Faces and Voices.Evolutionary Psychology8447461

27. Feinberg DR, DeBruine LM, Jones BC, Perrett DI (2008) The role of femininity and averageness of voice pitch in aesthetic judgments of women's voices. Perception 37: 615–623.DR FeinbergLM DeBruineBC JonesDI Perrett2008The role of femininity and averageness of voice pitch in aesthetic judgments of women's voices.Perception37615623

28. Puts DA, Barndt JL, Welling LLM, Dawood K, Burriss RP (2011) Intrasexual competition among women Vocal femininity affects perceptions of attractiveness and flirtatiousness. Pers Indiv Differ 50: 111–115.DA PutsJL BarndtLLM WellingK. DawoodRP Burriss2011Intrasexual competition among women Vocal femininity affects perceptions of attractiveness and flirtatiousness.Pers Indiv Differ50111115

29. O'Connor JJM, Re DE, Feinberg DR (2011) Voice Pitch Influences Perceptions of Sexual Infidelity. Evolutionary Psychology 9: 64–78.JJM O'ConnorDE ReDR Feinberg2011Voice Pitch Influences Perceptions of Sexual Infidelity.Evolutionary Psychology96478

30. Fraccaro PJ, Jones BC, Vukovic J, Smith FG, Watkins CD, et al. (2011) Experimental evidence that women speak in a higher voice pitch to men they find attractive. J Evol Psychol 9: 57–67.PJ FraccaroBC JonesJ. VukovicFG SmithCD Watkins2011Experimental evidence that women speak in a higher voice pitch to men they find attractive.J Evol Psychol95767

31. Borkowska P, Pawlowski B (2011) Female voice frequency in the context of dominance and attractiveness perception. Anim Behav 82: 55–59.P. BorkowskaB. Pawlowski2011Female voice frequency in the context of dominance and attractiveness perception.Anim Behav825559

32. Andersson M (1994) Sexual Selection. Princeton, NJ: Princeton University Press. M. Andersson1994Sexual SelectionPrinceton, NJPrinceton University Press

33. Moore BCJ (1995) Hearing. San Diego, CA: Academic Press. BCJ Moore1995HearingSan Diego, CAAcademic Press

34. Feinberg DR, DeBruine LM, Jones BC, Little AC (2008) Correlated preferences for men's facial and vocal masculinity. Evol Hum Behav 29: 233–241.DR FeinbergLM DeBruineBC JonesAC Little2008Correlated preferences for men's facial and vocal masculinity.Evol Hum Behav29233241

35. Smith DR, Walters TC, Patterson RD (2007) Discrimination of speaker sex and size when glottal-pulse rate and vocal-tract length are controlled. J Acoust Soc Am 122: 3628–3639.DR SmithTC WaltersRD Patterson2007Discrimination of speaker sex and size when glottal-pulse rate and vocal-tract length are controlled.J Acoust Soc Am12236283639

36. Kawahara H, Matsui H (2003) Auditory morphing based on an elastic perceptual distance metric in an interference-free time-frequency representation. 2003 Ieee International Conference on Acoustics, Speech, and Signal Processing, Vol I, Proceedings 256–259.H. KawaharaH. Matsui2003Auditory morphing based on an elastic perceptual distance metric in an interference-free time-frequency representation.2003 Ieee International Conference on Acoustics, Speech, and Signal Processing, Vol I, Proceedings256259

37. Lui C, Kewley-Port D (2004) STRAIGHT: A new speech synthesizer for vowel formant discrimination. Acoustic Research Letters Online 5: 31–36.C. LuiD. Kewley-Port2004STRAIGHT: A new speech synthesizer for vowel formant discrimination.Acoustic Research Letters Online53136

38. Charpentier F, Moulines E (1989) Pitch-synchronous waveforms processing techniques for text-to-speech synthesis using diphones. Proceedings of Eurospeech. pp. 13–19.F. CharpentierE. Moulines1989Pitch-synchronous waveforms processing techniques for text-to-speech synthesis using diphones.Proceedings of Eurospeech1319

39. Boersma P, Weenink D (2009) Praat: doing phonetics by computer (Version 5.1.04).P. BoersmaD. Weenink2009Praat: doing phonetics by computer (Version 5.1.04).

40. Jones BC, Feinberg DR, DeBruine LM, Little AC, Vukovic J (2008) Integrating cues of social interest and voice pitch in men's preferences for women's voices. Biol Letters 4: 192–194.BC JonesDR FeinbergLM DeBruineAC LittleJ. Vukovic2008Integrating cues of social interest and voice pitch in men's preferences for women's voices.Biol Letters4192194

41. Vukovic J, Feinberg DR, Jones BC, DeBruine LM, Welling LLM, et al. (2008) Self-rated attractiveness predicts individual differences in women's preferences for masculine men's voices. Pers Indiv Differ 45: 451–456.J. VukovicDR FeinbergBC JonesLM DeBruineLLM Welling2008Self-rated attractiveness predicts individual differences in women's preferences for masculine men's voices.Pers Indiv Differ45451456

42. Reby D, McComb K, Cargnelutti B, Darwin C, Fitch WT, et al. (2005) Red deer stags use formants as assessment cues during intrasexual agonistic interactions. P R Soc 272: 941–947.D. RebyK. McCombB. CargneluttiC. DarwinWT Fitch2005Red deer stags use formants as assessment cues during intrasexual agonistic interactions.P R Soc272941947

43. Fitch WT, Fritz JB (2006) Rhesus macaques spontaneously perceive formants in conspecific vocalizations. J Acoust Soc Am 120: 2132–2141.WT FitchJB Fritz2006Rhesus macaques spontaneously perceive formants in conspecific vocalizations.J Acoust Soc Am12021322141

44. Gescheider GA (1997) Psychophysics: The fundamentals. New Jersey: Lawrence Erlbaum Associates. GA Gescheider1997Psychophysics: The fundamentalsNew JerseyLawrence Erlbaum Associates

45. Flanagan JL, Saslow MG (1957) Pitch discrimination for Synthetic Vowels. J Acoust Soc Am 30: 7.JL FlanaganMG Saslow1957Pitch discrimination for Synthetic Vowels.J Acoust Soc Am307

46. Klatt DH (1973) Discrimination of fundamental frequency contours in synthetic speech: implications for models of pitch perception. J Acoust Soc Am 53: 8.DH Klatt1973Discrimination of fundamental frequency contours in synthetic speech: implications for models of pitch perception.J Acoust Soc Am538

47. Smith DRR, Patterson RD, Turner R, Kawahara H, Irino T (2005) The processing and perception of size information in speech sounds. J Acoust Soc Am 117: 305–318.DRR SmithRD PattersonR. TurnerH. KawaharaT. Irino2005The processing and perception of size information in speech sounds.J Acoust Soc Am117305318

48. Luce RD, Green DM (1978) 2 Tests of a Neural Attention Hypothesis for Auditory Psychophysics. Percept Psychophys 23: 363–371.RD LuceDM Green19782 Tests of a Neural Attention Hypothesis for Auditory Psychophysics.Percept Psychophys23363371

49. Griffiths TD, Rees A, Witton C, Cross PM, Shakir RA, et al. (1997) Spatial and temporal auditory processing deficits following right hemisphere infarction - A psychophysical study. Brain 120: 785–794.TD GriffithsA. ReesC. WittonPM CrossRA Shakir1997Spatial and temporal auditory processing deficits following right hemisphere infarction - A psychophysical study.Brain120785794

50. Moore BCJ, Peters RW (1992) Pitch Discrimination and Phase Sensitivity in Young and Elderly Subjects and Its Relationship to Frequency-Selectivity. J Acoust Soc Am 91: 2881–2893.BCJ MooreRW Peters1992Pitch Discrimination and Phase Sensitivity in Young and Elderly Subjects and Its Relationship to Frequency-Selectivity.J Acoust Soc Am9128812893

51. Klinge A, Klump GM (2009) Frequency difference limens of pure tones and harmonics within complex stimuli in Mongolian gerbils and humans. J Acoust Soc Am 125: 304–314.A. KlingeGM Klump2009Frequency difference limens of pure tones and harmonics within complex stimuli in Mongolian gerbils and humans.J Acoust Soc Am125304314

52. Smith DRR, Patterson RD (2005) The interaction of glottal-pulse rate and vocal-tract length in judgements of speaker size, sex, and age. J Acoust Soc Am 118: 3177–3186.DRR SmithRD Patterson2005The interaction of glottal-pulse rate and vocal-tract length in judgements of speaker size, sex, and age.J Acoust Soc Am11831773186

53. Pisanski K, Rendall D (2011) The prioritization of voice fundamental frequency or formants in listeners' assessments of speaker size, masculinity, and attractiveness. J Acoust Soc Am 129: 12.K. PisanskiD. Rendall2011The prioritization of voice fundamental frequency or formants in listeners' assessments of speaker size, masculinity, and attractiveness.J Acoust Soc Am12912

54. Stevens SS (1951) Handbook of experimental psychology. New York: John Wiley and Sons Inc.. SS Stevens1951Handbook of experimental psychologyNew YorkJohn Wiley and Sons Inc.

55. Motulskey H, Christopolous A (2004) Fitting Models to Biological Data Using Linear and Non-linear Regression: A Practical Guide to Curve Fitting. Oxford: Oxford University Press. H. MotulskeyA. Christopolous2004Fitting Models to Biological Data Using Linear and Non-linear Regression: A Practical Guide to Curve FittingOxfordOxford University Press

56. Collins SA, Missing C (2003) Vocal and visual attractiveness are related in women. Anim Behav 65: 997.SA CollinsC. Missing2003Vocal and visual attractiveness are related in women.Anim Behav65997

57. Feinberg D, DeBruine L, Jones B, Perrett D (2008) The role of femininity and averageness of voice pitch in aesthetic judgments of women's voices. Perception 37: 615–623.D. FeinbergL. DeBruineB. JonesD. Perrett2008The role of femininity and averageness of voice pitch in aesthetic judgments of women's voices.Perception37615623

58. Jones BC, Feinberg DR, Debruine LM, Little AC, Vukovic J (2008) Integrating cues of social interest and voice pitch in men's preferences for women's voices. Biol Lett 4: 192–194.BC JonesDR FeinbergLM DebruineAC LittleJ. Vukovic2008Integrating cues of social interest and voice pitch in men's preferences for women's voices.Biol Lett4192194

59. Jones BC, Feinberg DR, DeBruine LM, Little AC, Vukovic J (2010) A domain-specific opposite-sex bias in human preferences for manipulated voice pitch. Anim Behav 79: 57–62.BC JonesDR FeinbergLM DeBruineAC LittleJ. Vukovic2010A domain-specific opposite-sex bias in human preferences for manipulated voice pitch.Anim Behav795762

60. O'Connor J, Re D, Feinberg D (2011) Voice Pitch Influences Perceptions of Sexual Infidelity. Evolutionary Psychology 9: 64–78.J. O'ConnorD. ReD. Feinberg2011Voice Pitch Influences Perceptions of Sexual Infidelity.Evolutionary Psychology96478

61. Vukovic J, Feinberg DR, DeBruine LM, Smith FG, Jones BC (2010) Women's voice pitch is negatively correlated with health risk factors. J Evol Psychol 21: 767–772.J. VukovicDR FeinbergLM DeBruineFG SmithBC Jones2010Women's voice pitch is negatively correlated with health risk factors.J Evol Psychol21767772

62. Sorensen D, Horii Y (1982) Cigarette-Smoking and Voice Fundamental-Frequency. J Commun Disord 15: 135–144.D. SorensenY. Horii1982Cigarette-Smoking and Voice Fundamental-Frequency.J Commun Disord15135144

63. Gilbert HR, Weismer GG (1974) Effects of Smoking on Speaking Fundamental Frequency of Adult Women. J Psycholinguist Res 3: 225–231.HR GilbertGG Weismer1974Effects of Smoking on Speaking Fundamental Frequency of Adult Women.J Psycholinguist Res3225231

64. Aronson AE (1990) Clinical Disorders of the Voice. New York: Thieme Medical Publishers. AE Aronson1990Clinical Disorders of the VoiceNew YorkThieme Medical Publishers

65. Benjamin BJ (1981) Frequency Variability in the Aged Voice. J Gerontol 36: 722–726.BJ Benjamin1981Frequency Variability in the Aged Voice.J Gerontol36722726

66. Nishio M, Niimi S (2008) Changes in speaking fundamental frequency characteristics with aging. Folia Phoniatr Logo 60: 120–127.M. NishioS. Niimi2008Changes in speaking fundamental frequency characteristics with aging.Folia Phoniatr Logo60120127

67. Farrell ME, Briefer E, McElligott AG (2011) Assortative Mating in Fallow Deer Reduces the Strength of Sexual Selection. Plos One 6: ME FarrellE. BrieferAG McElligott2011Assortative Mating in Fallow Deer Reduces the Strength of Sexual Selection.Plos One6

68. Hari R, Hamalainen M, Ilmoniemi R, Kaukoranta E, Reinikainen K, et al. (1984) Responses of the Primary Auditory-Cortex to Pitch Changes in a Sequence of Tone Pips - Neuromagnetic Recordings in Man. Neurosci Lett 50: 127–132.R. HariM. HamalainenR. IlmoniemiE. KaukorantaK. Reinikainen1984Responses of the Primary Auditory-Cortex to Pitch Changes in a Sequence of Tone Pips - Neuromagnetic Recordings in Man.Neurosci Lett50127132

69. Cohen RM, Semple WE, Gross M, King AC, Nordahl TE (1992) Metabolic Brain Pattern of Sustained Auditory-Discrimination. Exp Brain Res 92: 165–172.RM CohenWE SempleM. GrossAC KingTE Nordahl1992Metabolic Brain Pattern of Sustained Auditory-Discrimination.Exp Brain Res92165172

70. Belin P, Zatorre RJ, Lafaille P, Ahad P, Pike B (2000) Voice-selective areas in human auditory cortex. Nature 403: 309–312.P. BelinRJ ZatorreP. LafailleP. AhadB. Pike2000Voice-selective areas in human auditory cortex.Nature403309312

71. Balleine BW, Delgado MR, Hikosaka O (2007) The role of the dorsal striatum in reward and decision-making. J Neurosci 27: 8161–8165.BW BalleineMR DelgadoO. Hikosaka2007The role of the dorsal striatum in reward and decision-making.J Neurosci2781618165

72. Belin P, Fecteau S, Bedard C (2004) Thinking the voice: neural correlates of voice perception. Trends Cogn Sci 8: 129–135.P. BelinS. FecteauC. Bedard2004Thinking the voice: neural correlates of voice perception.Trends Cogn Sci8129135

73. Puts DA, Hodges CR, Cardenas RA, Gaulin SJC (2007) Men's voices as dominance signals: vocal fundamental and formant frequencies influence dominance attributions among men. Evol Hum Behav 28: 340–344.DA PutsCR HodgesRA CardenasSJC Gaulin2007Men's voices as dominance signals: vocal fundamental and formant frequencies influence dominance attributions among men.Evol Hum Behav28340344

74. Bruckert L, Lienard JS, Lacroix A, Kreutzer M, Leboucher G (2006) Women use voice parameters to assess men's characteristics. P R Soc B 273: 83–89.L. BruckertJS LienardA. LacroixM. KreutzerG. Leboucher2006Women use voice parameters to assess men's characteristics.P R Soc B2738389

75. Geary DC, Vigil J, Byrd-Craven J (2004) Evolution of human mate choice. J Sex Res 41: 27–42.DC GearyJ. VigilJ. Byrd-Craven2004Evolution of human mate choice.J Sex Res412742

76. Bruckert L, Bestelmeyer P, Latinus M, Rouger J, Charest I, et al. (2010) Vocal Attractiveness Increases by Averaging. Current Biology 20: 116–120.L. BruckertP. BestelmeyerM. LatinusJ. RougerI. Charest2010Vocal Attractiveness Increases by Averaging.Current Biology20116120

77. Feinberg DR, Jones BC, DeBruine LM, O'Connor JJM, Tigue CC, et al. (2011) Integrating fundamental and formant frequencies in women's preferences for men's voices. Behavioral Ecology 22: 1320–1325.DR FeinbergBC JonesLM DeBruineJJM O'ConnorCC Tigue2011Integrating fundamental and formant frequencies in women's preferences for men's voices.Behavioral Ecology2213201325