5D Library › 嗓音生物力学、非线性源-滤波耦合与听觉-运动反馈的数学模型 · English

第六章 隆巴德效应与骨导—气导混合监听

一个百年的反射

第 10 本第三章介绍了隆巴德效应。本章看它在歌唱中的两种处境——响亮的伴奏,以及耳塞或返听耳机——因为它们改变了第五章那个回路的输入。

证据

法国耳鼻喉科医生隆巴德 1911 年报告了「提高嗓音的征象」:说话者在噪声中会提高音量 (Lombard 1911)。莱恩与特拉内尔 1971 年的经典综述把隆巴德效应与「侧音」效应放在一起讨论:前者是听到的噪声越大、说话越响;后者是听到的自己的声音被放大时,说话变轻;两者都说明说话者在用耳朵调节音量 (Lane and Tranel 1971)。此后在多种鸟类与哺乳动物中都发现了这一效应,它是听觉反馈塑造发声最稳健的例子之一 (Zollinger and Brumm 2011; Brumm and Zollinger 2011)。皮克等人发现,隆巴德效应「极其稳定而稳健」:单靠指令几乎不能使未受训练的说话者抑制它;提供显示声强的视觉反馈后,受试者才学会抑制,而且撤去反馈后仍能保持——但他们主要是整体降低了音量,而不是改变了对噪声的反应方式 (Pick et al. 1989)。在合唱中也观察到了隆巴德效应 (Tonkinson 1994)。

证据

加尼耶、昂里克与迪布瓦比较了通过耳机与通过扬声器播放噪声的条件:耳机使说话者「沉浸」在噪声中,嗓音的变化更大;在耳机中加入说话者自己声音的返送可以减小这种差别,但不能完全抵消。他们还发现,有交流对象时的嗓音调整与独自朗读时不同 (Garnier et al. 2010)。

两条路,一个耳蜗

歌者听到自己的声音有两条路:气导——声音从嘴唇出来,绕过脸颊进入外耳道;骨导——声带振动经颅骨与软组织直接传到内耳。

证据

赖因费尔特等人比较了十个音素发声时自身声音的骨导与气导成分,发现对大多数音素,骨导部分在 1–2 kHz 之间占优,不同音素因发声方式不同而略有差别 (Reinfeldt et al. 2010)。当外耳道被堵住时,骨导传入外耳道的低频声音不再能从耳道口逸出,耳道内的低频声压升高,即堵耳效应;施滕费尔特与赖因费尔特的模型与测量显示,堵耳效应在各种堵塞深度下都存在,入耳式耳机在低频产生的堵耳效应大于压耳式耳机 (Stenfelt and Reinfeldt 2007)。

这里有一个常被忽略的物理事实:气导与骨导的自身声音在同一个耳蜗里相加。外界的伴奏声经由气导到达同一个耳蜗,同时掩蔽这两部分自身声音。所以「靠骨导听自己」并不是一条绕开掩蔽的独立通道。耳塞与返听耳机真正改变的是比例:它们把外界声音与气导的自身声音一起衰减,却放过(并在低频放大)骨导的自身声音。

下面的程序按频带算这笔账:自身声音的气导与骨导成分、伴奏、耳塞或返听耳机的隔声与堵耳效应,以及返听耳机中自身声音的混音增益。每个频带的「自身声音与伴奏之比」决定那个频带的音高分辨精度,各频带按方差倒数合并;最后与一个精度较低、但不受噪声影响的体感通道融合(稳态卡尔曼权重)。所有声级都是示意假设。

推导

# Hearing yourself through air and bone in loud accompaniment, band by band
# (illustrative). Air- (AC) and bone-conducted (BC) own voice add up in the SAME cochlea;
# outside noise masks both. Plugs cut AC voice and band by 20 dB and boost BC at low
# frequencies (occlusion); in-ear monitors isolate 25 dB and add the own voice back at mix
# gain m dB. Band pitch sd = 6 cents x (1 + 10^(-SNR/10)), combined by inverse variance,
# then fused with a noise-free laryngeal/vibrotactile sense (sd 25 cents, assumed).
import math

BANDS = (250, 500, 1000, 2000, 4000)
VOICE_AC = (78, 82, 80, 74, 66)            # own voice by air, open ear
# bone path relative to air (BC dominant at 1-2 kHz)
BC_RE_AC = (-6, -3, 2, 3, -10)
OCCL = (15, 10, 3, 0, 0)                   # occlusion boost of the bone path, ear shut
ORCH = (92, 94, 90, 82, 74)                # loud band at the singer's ear
SD_SOMA = 25.0
db_sum = lambda *ls: 10 * math.log10(sum(10 ** (v / 10) for v in ls))

def condition(kind, mix=0.0):
    rows = []
    for i in range(len(BANDS)):
        ac, bc, noise = VOICE_AC[i], VOICE_AC[i] + BC_RE_AC[i], ORCH[i]
        if kind == "quiet":
            noise = 30.0
        elif kind in ("plugs", "iem"):
            cut = 20 if kind == "plugs" else 25
            ac, noise, bc = ac - cut, noise - cut, bc + OCCL[i]
            if kind == "iem":
                ac = db_sum(ac, VOICE_AC[i] + mix)         # monitor feed of the own voice
        rows.append((db_sum(ac, bc) - noise, 1 / (1 + 10 ** ((bc - ac) / 10))))
    sds = [6.0 * (1 + 10 ** (-snr / 10)) for snr, _ in rows]
    sd_aud = 1 / math.sqrt(sum(1 / s ** 2 for s in sds))
    prec = 1 / sd_aud ** 2 + 1 / SD_SOMA ** 2
    return rows, sd_aud, (1 / sd_aud ** 2) / prec, 1 / math.sqrt(prec)

print("SNR = own voice minus accompaniment at the cochlea (dB, 250 / 1k / 4k Hz);")
print("air = share of own voice arriving by air; sd in cents; w = weight on hearing")
print("condition             |  250    1k    4k  | air  | hear  |  w   | fused")
CASES = (("quiet room", "quiet", 0), ("open ears, loud band", "open", 0),
         ("foam ear plugs", "plugs", 0), ("in-ear monitor -10 dB", "iem", -10),
         ("in-ear monitor +0 dB", "iem", 0), ("in-ear monitor +6 dB", "iem", 6))
for name, kind, mix in CASES:
    rows, sd_aud, w, sd_f = condition(kind, mix)
    snrs = " ".join(f"{rows[i][0]:+5.1f}" for i in (0, 2, 4))
    air = sum(a for _, a in rows) / len(rows)
    print(f"{name:22s}| {snrs} | {air:4.0%} | {sd_aud:5.1f} | {w:.2f} | {sd_f:5.1f}")
# SNR = own voice minus accompaniment at the cochlea (dB, 250 / 1k / 4k Hz);
# air = share of own voice arriving by air; sd in cents; w = weight on hearing
# condition             |  250    1k    4k  | air  | hear  |  w   | fused
# quiet room            | +49.0 +54.1 +36.4 |  62% |   2.7 | 0.99 |   2.7
# open ears, loud band  | -13.0  -5.9  -7.6 |  62% |  14.2 | 0.76 |  12.4
# foam ear plugs        | +15.0 +15.0  +2.4 |   2% |   2.9 | 0.99 |   2.9
# in-ear monitor -10 dB | +20.1 +20.1 +10.1 |  12% |   2.8 | 0.99 |   2.7
# in-ear monitor +0 dB  | +20.5 +21.2 +17.4 |  35% |   2.7 | 0.99 |   2.7
# in-ear monitor +6 dB  | +21.8 +23.5 +23.1 |  60% |   2.7 | 0.99 |   2.7

结果可以分成四种处境来读。

安静的房间:自身声音高出环境噪声 36–54 dB,听觉估计的标准差约 2.7 音分,自身声音中约 62% 来自气导。

张开耳朵、响亮的乐队:自身声音在各频带都低于伴奏 6–13 dB,听觉估计的标准差升到 14.2 音分;融合后体感通道获得约四分之一的权重(听觉权重 0.76),合并的标准差为 12.4 音分。这就是第五章假说所说的「掩蔽下体感权重上升」在模型中的样子。

泡沫耳塞:伴奏与气导的自身声音都衰减 20 dB,骨导的自身声音却在低频被堵耳效应放大,于是自身声音与伴奏之比在中低频回到约 +15 dB(4 kHz 约 +2 dB),听觉精度恢复到 2.9 音分。代价是,到达耳蜗的自身声音只有约 2% 来自气导:歌者听到的几乎完全是一个低频被放大、高频较弱的骨导声音,与听众听到的声音相去甚远。

返听耳机:隔声更好,再把麦克风拾取的自身声音混入耳机。混音增益从 −10 dB 提高到 +6 dB,气导所占比例从 12% 回到 60%,接近张开耳朵时的 62%,同时在中低频保持约 +20 dB 的信噪比。也就是说,返听混音的意义不只是「更响」,而是恢复自身声音中气导与骨导的自然比例。

听到的变了,唱法也会变

如果歌者用耳朵调节音量,那么改变他听到的东西,就会改变他唱出来的东西。下面的程序用两条假设的斜率(隆巴德与侧音各为每分贝 0.5 分贝)估计四种监听条件下的嗓音级,以及传到听众席的歌声与乐队之比。

推导

# Lombard and sidetone effects with open ears, plugs and in-ear monitors (illustrative
# regulation model, not fitted). Vocal level V (dB re open ears in quiet):
#   V = sL * max(0, N_heard - N0) - sS * (self_heard - self_open),  sL = sS = 0.5 ASSUMED
# The audience hears the singer by air only: plugs change what the singer hears, not the
# hall.
import math

# band at the ear (dB), Lombard onset, slopes
N_BAND, N0, SL, SS = 94.0, 45.0, 0.5, 0.5
# own voice at the cochlea by path, open ear (dB)
AIR, BONE = 85.0, 83.0
db_sum = lambda *ls: 10 * math.log10(sum(10 ** (v / 10) for v in ls))
SELF_OPEN = db_sum(AIR, BONE)

# 20 / 25 dB isolation; occlusion +8 dB on bone
def voice_level(kind, mix=0.0):
    n, s = {"open": (N_BAND, SELF_OPEN),
            "plugs": (N_BAND - 20, db_sum(AIR - 20, BONE + 8)),
            "iem": (N_BAND - 25, db_sum(AIR - 25, BONE + 8, AIR + mix))}[kind]
    return SL * max(0.0, n - N0) - SS * (s - SELF_OPEN), n, s

print(f"accompaniment {N_BAND:.0f} dB at the ear; slopes sL = sS = {SL} dB/dB (assumed)")
print("condition            | band heard | own voice heard | vocal level | to the hall*")
v_open = voice_level("open")[0]
CASES = (("open ears", "open", 0), ("foam ear plugs", "plugs", 0),
         ("in-ear, own mix -6 dB", "iem", -6), ("in-ear, own mix +6 dB", "iem", 6))
for name, kind, mix in CASES:
    v, n, s = voice_level(kind, mix)
    print(f"{name:21s}|  {n:5.1f} dB  |   {s - SELF_OPEN:+5.1f} dB      |  {v:+5.1f} dB  "
          f"  | {v - v_open:+5.1f} dB")
print("* change in the singer-to-band ratio in the hall, relative to open ears")
print(f"in a quiet room (30 dB) the model predicts no Lombard rise "
      f"({SL * max(0.0, 30 - N0):+.1f} dB)")
# accompaniment 94 dB at the ear; slopes sL = sS = 0.5 dB/dB (assumed)
# condition            | band heard | own voice heard | vocal level | to the hall*
# open ears            |   94.0 dB  |    +0.0 dB      |  +24.5 dB    |  +0.0 dB
# foam ear plugs       |   74.0 dB  |    +3.9 dB      |  +12.6 dB    | -11.9 dB
# in-ear, own mix -6 dB|   69.0 dB  |    +4.1 dB      |   +9.9 dB    | -14.6 dB
# in-ear, own mix +6 dB|   69.0 dB  |    +6.9 dB      |   +8.6 dB    | -15.9 dB
# * change in the singer-to-band ratio in the hall, relative to open ears
# in a quiet room (30 dB) the model predicts no Lombard rise (+0.0 dB)

在 94 dB 的伴奏中张开耳朵演唱,模型预测歌者的嗓音级比安静时提高约 24.5 dB——这是一个需要警惕的嗓音负荷。戴上泡沫耳塞后,歌者听到的乐队降到 74 dB,又因堵耳效应听到自己更响(+3.9 dB),于是嗓音级只提高 12.6 dB;但听众席并没有戴耳塞,传到听众的歌声与乐队之比因此下降约 12 dB。返听耳机在两种混音下下降约 15–16 dB。这个结果的方向——隔声与堵耳使歌者唱得更轻——与侧音效应和加尼耶等人的观察一致;它的大小完全取决于假设的斜率,不能当作预测。

取舍很实际:隔声保护听力、减轻嗓音负荷、让音高更易听清,但歌者需要另外的线索(音响师、录音回放、有意识的校准)才能知道自己在听众席的效果。

注

这不是听力或耳科建议。 耳塞与返听耳机首先是保护听力的工具,长期在响亮环境中演出的人应当使用合适的听力保护,并咨询听力师。本章的计算只讨论它们对自我监听的声学影响;入耳式设备的佩戴、音量设置与听力检查请遵从专业人员的意见。

假说 · 尚未验证

单耳半堵假说(尚未确立)。在合唱中,用手掌轻轻盖住一只耳朵(另一只耳朵张开)的歌者,与两耳都张开时相比,音高误差更小,而嗓音级的提高也更少;与两耳都堵住时相比,听众感知的音色变化更小。可以检验的预测:在一项合唱团员自身对照的随机交叉研究中,单耳半堵条件下的平均绝对音高误差低于两耳张开,嗓音级低于两耳张开、高于两耳堵住。如果单耳半堵在音高误差上与两耳张开没有差别,这一假说就被推翻。(第八章核查表第四步用的是这一思路的个人版本。)

本章小结

隆巴德效应是稳健、近乎自动的反射:噪声越大说话越响,听到自己越响说话越轻;单靠指令难以抑制,需要反馈训练。歌者的自身声音经气导与骨导在同一个耳蜗相加(骨导在 1–2 kHz 占优),外界噪声同时掩蔽两者。示意计算显示:在响亮的乐队中张开耳朵,自身声音低于伴奏 6–13 dB,音高估计变差,体感权重上升;耳塞恢复了信噪比,却使听到的自身声音几乎全部来自骨导;返听混音可以恢复气导与骨导的自然比例。隔声还会使歌者唱得更轻,传到听众的歌声与乐队之比下降——方向可靠,大小取决于假设。下一章离开测量,读几段古人关于歌唱与聆听的文字。

参考文献

Brumm, Henrik, and Sue Anne Zollinger. 2011. “The Evolution of the Lombard Effect: 100 Years of Psychoacoustic Research.” Behaviour 148 (11–13): 1173–98.
Garnier, Maëva, Nathalie Henrich, and Danièle Dubois. 2010. “Influence of Sound Immersion and Communicative Interaction on the Lombard Effect.” Journal of Speech, Language, and Hearing Research 53 (3): 588–608. https://doi.org/10.1044/1092-4388(2009/08-0138).
Lane, Harlan, and Bernard Tranel. 1971. “The Lombard Sign and the Role of Hearing in Speech.” Journal of Speech and Hearing Research 14 (4): 677–709. https://doi.org/10.1044/jshr.1404.677.
Lombard, Étienne. 1911. “Le Signe de l’élévation de La Voix.” Annales Des Maladies de l’Oreille, Du Larynx, Du Nez Et Du Pharynx 37 (2): 101–19.
Pick, Herbert L., Gerald M. Siegel, Paul W. Fox, Sharon R. Garber, and Joseph K. Kearney. 1989. “Inhibiting the Lombard Effect.” Journal of the Acoustical Society of America 85 (2): 894–900. https://doi.org/10.1121/1.397561.
Reinfeldt, Sabine, Per Östli, Bo Håkansson, and Stefan Stenfelt. 2010. “Hearing One’s Own Voice During Phoneme Vocalization: Transmission by Air and Bone Conduction.” Journal of the Acoustical Society of America 128 (2): 751–62. https://doi.org/10.1121/1.3458855.
Stenfelt, Stefan, and Sabine Reinfeldt. 2007. “A Model of the Occlusion Effect with Bone-Conducted Stimulation.” International Journal of Audiology 46 (10): 595–608. https://doi.org/10.1080/14992020701545880.
Tonkinson, S. 1994. “The Lombard Effect in Choral Singing.” Journal of Voice 8 (1): 24–29.
Zollinger, Sue Anne, and Henrik Brumm. 2011. “The Lombard Effect.” Current Biology 21 (16): R614–15.

Fan, Y. (2026). Vocal Biomechanics, Non-Linear Source-Filter Coupling and Auditory-Motor Feedback: From Titze's Self-Sustained Vocal Fold Oscillation and Vocal-Tract Inertance to the Lombard Effect, Read Beside Classical Chinese Vocal Aesthetics [嗓音生物力学、非线性源-滤波耦合与听觉-运动反馈的数学模型] (Version 1.0.0). 5D Library. https://doi.org/10.5281/zenodo.23770084 · Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0).