Insights into spoken language gleaned from phonetic transcription of the Switchboard corpus

INSIGHTS INTO SPOKEN LANGUAGE GLEANED FROM PHONETIC TRANSCRIPTION OF THE SWITCHBOARD CORPUS

Steven Greenberg, Joy Hollenback, Dan Ellis

University of California, Berkeley

International Computer Science Institute

1947 Center Street, Berkeley, CA 94704 USA

ABSTRACT

Models of speech recognition (by both human and machine) have traditionally assumed the phoneme to serve as the fundamental unit of phonetic and phonological analysis. However, phoneme-centric models have failed to provide a convincing theoretical account of the process by which the brain extracts meaning from the speech signal and have fared poorly in automatic recognition of natural, informal speech (e.g., the Switchboard corpus).

Over the past five months the Switchboard Transcription Project has phonetically transcribed a portion of the Switchboard corpus in an effort to better understand the failure of phoneme-centric models for machine recognition of speech, as well as to provide a database through which to improve the performance of recognition systems focused on conversational dialogs.

Transcription of spoken dialogs illustrates the pitfalls of a phoneme-based system. Many words are articulated in such a fashion as to either omit or significantly transform the phonetic properties of phonemic constituents, thus resulting in wide variation of word pronunciations. Often, only the barest hint of a segment is realized phonetically, in spite of good intelligibility.

Despite this large variability in phonetic realization of words, the temporal properties of speech segments, both phones and syllables, appear to conform to regular patterns. This temporal regularity suggests that much of the linguistic information in speech may be signaled through variations in amplitude, pitch and the coarse spectrum, and that such patterns may be useful in the design of future-generation speech recognition systems.

1. INTRODUCTION

Models of speech perception and recognition focus on the phone(me) as the basic representational unit from which lexical units are ultimately derived. Although this representational model often provides an adequate (if not completely comprehensive) descriptive basis for the acoustics of carefully articulated and read speech, it fails to capture many of the spectro-temporal properties of spontaneous speech typical of informal spoken dialog.

The Switchboard corpus provides an excellent test-bed with which to compare the phonetic properties of spontaneous speech with those characteristic of more formal speaking situations as encapsulated by the TIMIT, ATIS and Wall Street Journal corpora. For the latter three corpora, performance by automatic speech recognition systems typically range between 85 and 98% correct. In contrast, material from the Switchboard corpus is typically recognized with only 40-60% accuracy.

In the Switchboard corpus two individuals discuss a specific topic, such as summer vacations, professional dress codes, the international political situation, credit cards and so on for several minutes over the telephone. The dialog contains a significant proportion of "filled pauses" (e.g., "um," "uh-huh", etc.), "misarticulations" (e.g., transpositions of specific phonetic segments), phonetic and lexical deletions ("University of Nebraska" being pronounced [yuw nix ver six n dix bclbrae skclkaeq], where the "of" is entirely deleted, and the final syllable of "University" [dix] delayed till after the initiation of the nasal consonant in "Nebraska").

Often, only the vaguest hint of the "appropriate" spectral cues are present in the spectrographic representation. Typically, formant transitions usually associated with specific segments (such as liquids or nasals) are either entirely missing or differ appreciably from the patterns observed in more formally articulated speech. Such deviations from the "canonical" phonetic representation pose a significant challenge to current models of speech recognition.

2. SWITCHBOARD TRANSCRIPTION

PROJECT

In order to more fully characterize the phonetics of spontaneous speech, seventy-two minutes of the Switchboard corpus (comprising portions of 618 conversations from 750 speakers, representing both genders, and spanning a wide range of adult ages and dialectal patterns from American English) were phonetically transcribed by a group of eight Linguistics students (7 undergraduates and 1 graduate student) all of whom had received previous training in phonetic transcription and general phonetics/phonology at the University of California, Berkeley. The transcribers were closely supervised by both the senior author and Professor John Ohala in order to insure as accurate and as uniform a transcription of the materials as possible. Specific transcription issues were discussed at weekly project meetings, using a 60" BARCO projection screen for computer display and audio feedback.

The phonetic transcriptions were encoded with a variant of the Arpabet transcription system used for the TIMIT corpus. This

transcription system was augmented with a set of diacritics representing such phonetic properties as glottalization ("creaky voice"), nasalization (typically applied to vocalic segments), frication, aspiration, de-voicing, unusual voicing, and velarization. In addition, transitional elements between adjacent vocalic or glide-like segments were explicitly marked. For each short span of speech, the time-domain waveform and its time-aligned wideband spectrographic representation were displayed on a color SparcStation using Entropics waves+ software. Below the spectrographic display was a forced-Viterbi (time) aligned and labeled transcription providing the transcribers with an "initial guess" as to the identity and temporal boundaries of each phonetic segment. Below this phonetic transcription was displayed the (time-aligned) word transcription associated with the speech signal. Transcribers used the initial Viterbi-aligned transcriptions only as a starting point, and typically modified (or moved), added and/or deleted segments and associated segmental boundaries, in accordance with their phonetic training.

3. ?PHONE FREQUENCIES

The phonetic transcription of Switchboard provides an opportunity to examine the frequency of occurrence of phonetic segments in informal speech. Table 1 lists the phonetic elements (stripped of their diacritical modification) for the transcribed portion of the corpus. The general patterns illustrated conform to previous accounts [e.g., 1]. Perhaps the most interesting observation is the relatively high frequency of the glottal stop [q] in spontaneous speech. Its frequency (ca.

1.5%) is in the midrange of occurrence for phonetic elements. The glottal stop has begun to function in place of many syllable-final (usually voiceless) stops and at the beginning of many syllable-initial vocalic segments. In this sense it often serves as an element to demarcate the beginning and ending of syllables.

1 -14 15 - 28 29 - 4

2 4

3 - 56

1n.0540dh.0243 v.0145 th.0076

2 s.0439ae.0239bcl.0144 nx.0069

3ih.0430ow.0232 ey.0142 aw.0066

4 ax.0420ay.0231 uh.0142 el.0048

5 iy.0359l.0219 q.013

6 sh.0047

6tcl.0356 w.0219 y.0134 ux.0047

7 ix.0354dcl.0218 dx.0132 jh.0046

8 t.0345z.0190 f.0131 ch.0044

9 eh.0309d.0189 ao.0130 en.0040

10 r.0299 er.0181 uw.0116axr.0034

11 ah.0295 aa.0177 hh.0102 oy.0011 12kcl.0266pcl.0163 g.0094 zh.0010

13 k.0261 p.0158 ng.0093 em.0008

14 m.0251 b.0149gcl.0078eng.0001 Table 1: The frequency of occurrence, in descending order, of each of the 56 phones used to transcribe the Switchboard corpus.

4. DURATIONAL PROPERTIES OF

PHONETIC ELEMENTS Phonetic transcription also provides a means to analyze the durational properties of the phonetic elements in the Switchboard corpus, based on temporal boundaries associated with nearly 23,000 segments. These data are illustrated in Table 2, on the following page.

The durational patterns revealed by these data are rather interesting. The median duration for most phonetic classes is 60-100 ms. Diphthongs (except [uw] and [iy]) tend to be slightly longer (generally 120-150 ms) while the flaps and glottal stop tend to be shorter (25-25 ms). The short duration of the latter classes is consistent with their association with syllabic boundaries. Diphthongs are generally located within the nucleus of a syllable and possess certain properties similar to vocalic segments followed by glides. Their relatively long duration is therefore not surprising.

Within the Arpabet transcription system stop consonants are partitioned into closure (e.g. [pcl]) and release (e.g., [p]) components. When their durations are combined (in this analysis the combination is performed on a group, rather than the more desirable individual basis) the median durations fall within the 60-100 ms range typical of most other phonetic classes.

5. SYLLABLE DURATIONS

A durational analysis was also performed for syllables, which, on average, contain ca. 2.5 phonetic segments per unit. The median duration for all syllables in the transcribed portion of the Switchboard corpus is 167 ms, with the 20% and 80% percentiles corresponding to 107.5 and 260 ms, respectively. There is a slight asymmetry favoring longer intervals in the distribution of durations (on a linear axis) that is reflected in the mean (190 ms) being ca. 33 ms greater than the median duration. When syllable durations are plotted on a log2scale, normalized to the mean, the distribution is approximately symmetric and Gaussian in shape.

Syllable duration can be conceptualized in terms of "modulation frequency," (e.g., a syllable duration of 200 ms is equivalent to a modulation frequency of 5 Hz, a syllable duration of 125 ms is equivalent to a modulation frequency of 8 Hz, etc.) for comparison with a standard acoustic measure used for studies of speech intelligibility [2]. Such a comparison is illustrated in Figure 1. The modulation spectrum for an octave-wide channel, arithmetically centered at 1.5 kHz, computed from a single speaker's discourse over a two-minute interval is shown and compared with that of the distribution of syllable durations (transformed into equivalent modulation frequencies). The similarity between the two measurements suggests that much of the energy in the modulation spectrum may be derived from syllabic segmentation. This association is of interest in light of recent demonstrations that speech intelligibility is crucially dependent on the preservation of the portion of the modulation spectrum between 2 and 10 Hz [3, 4, 5].

VOWELS 20% 50% 80% N Diphthongs

aw98.4133.7205.3(147)

ay87.6122.8180.4(532)

ey82.0112.1159.9(338)

ow84.2123.4187.2(528)

oy112.1146.1180.0(26)

iy57.783.2122.1(861)

uw61.294.6147.3(259) Monopthongs

aa75.7110.0149.4(404)

ao68.9102.0150.7(295)

ae80.5118.5185.5(620)

ih47.469.396.7(1057)

eh55.278.5107.3(733)

ah56.583.0127.8(682)

uh40.056.076.9(277)

ux44.565.288.8(89)

ax35.951.375.5(956)

ix35.151.476.3(660) Rotacized

axr55.680.2108.0(54)

er60.092.4134.9(423) Glides

w42.564.695.8(503)

y36.563.9100.4(354) CONSONANTS

Liquids

l40.860.084.1(532)

r39.565.095.4(668) Fricatives

sh92.8108.7142.0(108)

zh47.162.585.0(44)

f57.189.3118.6(308)

th48.969.590.1(170)

s60.089.1124.2(943)

v37.750.269.7(345)

dh23.840.460.5(534)

z48.669.8102.0(462)

hh40.062.289.4(223) Affricates

jh56.478.0111.7(93)

ch77.3107.7134.0(106) 20% 50% 80% N

Nasals

m50.668.488.6(569)

n37.656.081.9(1264)

ng42.865.7104.6(212)

Stops

b11.015.724.2(307)

bcl35.655.074.1(358) b+bcl46.670.798.3

d12.519.030.1(460)

dcl26.041.963.0(459)

d+dcl38.560.983.1

g20.128.240.0(210)

gcl27.541.561.1(184) g+gcl47.670.7101.1

p22.640.063.9(340)

pcl38.454.670.4(347) p+pcl61.084.6134.3

t20.638.962.2(808)

tcl23.139.761.0(783)

t+tcl43.778.6123.2

k27.046.370.1(610)

kcl28.345.261.0(588) k+kcl55.391.5131.1

q18.935.462.1(301)

Flaps

dx17.924.031.5(287)

nx21.326.832.9(131) SYLLABICS

Liquid

el63.089.2142.3(113) Nasals

em55.870.891.6(19)

en52.179.5112.6(92)

Table 2: Durations (in ms) for phone segments transcribed from a portion of the Switchboard corpus, partitioned into the 20th, 50th and 80th percentiles. N = number of instances for each phonetic class. Durational data for [eng] are omitted as a consequence of insufficient number of instances.

5101520

0.20.40.60.81Modulation Frequency (Hz)

M o d u l a t i o n E n e r g y Modulation Spectrum for 1 ? 2 kHz

05101520

0100

C o u n t

1/Syllable Duration (equiv. mod. freq.)

Figure 1: Frequency histogram for 2925 syllables derived from the Switchboard corpus (upper illustration). The modulation spectrum for two minutes of spoken discourse from a single speaker is shown in the lower illustration.

6. CONCLUSIONS

Detailed phonetic transcription of a spontaneous-speech corpus indicates that the spectral properties of many phonetic elements deviate significantly from their canonical form.Despite these spectral "abnormalities" such speech is almost always understandable, suggesting that other properties of the signal, such as segmental duration, may provide significant cues for intelligibility. Measurements of phonetic segment and syllable durations reveal a degree of temporal regularity that may serve as an important basis for understanding speech under a wide range of speaking conditions.

7. ACKNOWLEDGMENTS

The Switchboard Transcription Project (STP) was funded as part of the Speech Recognition Workshop held at the Center for Language and Speech Processing, Johns Hopkins University during the summer of 1996. STP was the product of many individuals' time and effort. We extend our appreciation and gratitude to Candace Cardinale, Melinda Chen, Rachel Coulston, Charles Gotcher, Mike McDaid, Diane Moffit,Colleen Richey and Gail Solomon who painstakingly transcribed the spoken-language materials. We would also like to extend our thanks to the following individuals for their efforts - John Ohala served as the "phonetician in residence" for the project and helped develop the transcription system and supervise the transcribers. Bob Weide provided useful advice concerning transcription systems. Eric Fosler and Jeff Bilmes provided valuable programming expertise during various stages of the project. Brian Kingsbury computed the modulation spectrum shown in Figure 1. Terri Durham, of the Oregon Graduate Institute, transcribed a portion of the corpus for us to compare and contrast with that of the Berkeley transcribers.Valuable discussion and advice was provided by many members of the ICSI Realization Group. Particular thanks are owed to Nelson Morgan and John Ohala for their counsel during the course of the project.

REFERENCES

1.Fletcher, H. (1953), Speech and Hearing in Communication , Princeton: van Nostrand.

2.

Houtgast, T and Steeneken, H. (1985) A review of the MTF concept in room acoustics and its use for estimating speech intelligibility in auditoria. J. Acoust. Soc. Am ,77, 1069-1077.

3.

Drullman R; Festen J. M. and Plomp, R. (1994) Effect of temporal envelope smearing on speech reception. J.Acoust. Soc. Am., 95, 1053-1064.

4.

Arai, T., Hermansky, H. Pavel, M. and Avendado, C.(1996) Intelligibility of speech with high-pass filtered time trajectories of spectral envelopes. Proc. ICSLP.5.

Greenberg, S. (1996) Understanding speech understanding: Towards a unified theory of speech perception. Proceedings of the ESCA Workshop on The Auditory Basis of Speech Perception, Keele University,pp. 1-8.

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文明网络演讲稿4篇 小泰温馨提示：演讲稿是在较为隆重的仪式上和某些公众场合发表的讲话文稿。演讲稿是进行演讲的依据，对演讲内容和形式的规范和提示，体现着演讲的目的和手段，用来交流思想、感情，表达主张、见解；也可以用来介绍自己的学习、工作情况和经验等等；同时具有宣传、鼓动、教育和欣赏等作用，可以把演讲者的观点、主张与思想感情传达给听众以及读者，使他们信服并在思想感情上产生共鸣。本文档根据演讲稿内容要求展开说明，具有实践指导意义，便于学习和使用，本文下载后内容可随意修改调整及打印。 本文简要目录如下：【下载该文档后使用Word打开，按住键盘Ctrl键且鼠标单击目录内容即可跳转到对应篇章】 1、篇章1：文明网络演讲稿 2、篇章2：网络文明演讲稿 3、篇章3：文明网络演讲稿 4、篇章4：英语之星的演讲稿网络文明 篇章1:文明网络演讲稿 遵守网络文明公约争做文明上网人

计算机互联网作为开放式信息传播和交流的工具，已经 走进了我们的学习和生活。从它刚刚兴起直到现在的风靡一时，年青的我们凭着对新鲜事物特有的接受能力，一直都是它忠实的应用者，无论是学习、休闲还是交流，网络都发挥了不可替代的作用。网络是把“双刃剑”在给我们带来利处的同时，由于我们辨别是非的经验不足，一些网络糟粕也随之侵袭着我们的心灵。到底怎么样才算是文明上网？反过来网络最大的文明又应该是什么？ 其实，关于网络所出现的问题，早已引起了家长、学校 和社会的关注，XX年11月，团中央等8个单位发布了《全国 青少年网络文明公约》，提倡"要善于网上学习，不浏览不良 信息；要诚实友好交流，不侮辱欺诈他人；要增强自我保护意识，不随意约会网友；要维护网络安全，不破坏网络秩序；要有益身心健康，不沉溺虚拟时空。"只要我们正确健康地上网，网络就会成为我们学习知识、交流思想、休闲娱乐的重要平台。现在，我们不仅学校有电脑，而且很多家庭都有了电脑，那我们在使用网络时该注意什么呢？ 善于网上学习，不浏览不良信息。现在人们对我们中学 生上网有一种普遍的看法：即不是玩游戏就是聊天。其实，网上学习，天地宽广。在网上学习，可以查关于学习的资料，也

中介语

中介语简介中介语理论是二语习得中的一个重要理论，它产生于20世纪70年代初并于80年代初被介绍到我国，对我国的外语教学产生了巨大的推动作用，人们也逐步认识到中介语在外语教学中的积极作用。Selinker在其论文Language Transfer （1969）中首次使用了“interlanguage”一词，并于1972发表了题为Interlanguage的研究论文。Selinker认为，中介语是第二语言学习者独立的语言系统，在结构上处于母语和目的语的中间状态（1972）。 中介语在英语学习中的干扰作用 一、中介语定义及特点 中介语（Interlanguage, 简称IL）一词是英国语言学家Selinker 1969 年首次提出. 现在又被译为过渡语、中间语、中继语、语际语等。它是指学习者在某一段时间内所创建的内在语言体系或学习者在整个学习过程中所构建的相互关联的语言体系。学习者在学习和使用第二语言时，不断接受和理解新的语音、语法知识，在此基础上逐渐形成自己的语言结构。并不断对其进行系统的预测调整，通过归纳和推论产生中介语。中介语的语言系统在结构上处于母语（Native Language）和目的语（Target Language）之间，具有独立性，并兼有两者的特点。综合国内外近来的研究,中介语有如下一些特征: 1．独立性 中介语是一个独立的语言系统，它既不同于母语, 又区别于外语, 也不能单纯的把它地看作外语学习过程中由于受母语的干扰而形成的混合体。中介语有其独特的语言规则，这些规则常常被学习者用来解释外语中固有而不规则的语言现象。 2．阶段性 中介语在逐渐进化的过程中，具有一定的阶段性。它是一个开放的体系，不是固定的一成不变的。这个体系在不断被新知识渗透的同时，修正原有知识，逐渐接近目的语。 3．动态性 在外语学习过程中，学习者的中介语在不断的发展变化。虽然它充满了错误，但由于新的语言规则有及强的扩展能力，它们处于不断的组合和变化中，因此中介语随着学习者的努力和交际需要而不断变化，由简而繁，由低而高，逐渐离开母语而接近目的语。如果我们设在母语与目的语之间的中介语为一个连续体，那么，在某一特定阶段，学习者的中介语可以用连续体上的某一点。中介语越接近目的语，说明学习者的外语水平越高。 4．系统性 中介语在每个阶段都表现出较强的系统性和内部一致性。它也是一个由内部要素构成的系统，就是说它有语音的、词汇的、语法的规则系统，而且自成体系。学习者对中介语的使

文明上网,从我做起(主题班会演讲稿)

男：同学们，在开班会之前，我们想问大家几个熟悉的问题：你的QQ号是多少？你的农场几级了？牧场呢？梦幻西游呢？ 女:现在随着中国社会的不断发展，人们的生活也逐渐富裕起来，网络也跟着在社会中流行，融入到了我们的生活中去，而且扩张的范围极大，尤其是对于中学生来说更是对“网络”爱不释手。 男：上个星期，我就问过几个中学生对告别网吧的看法，他们中的一些坚定的摇了头，并说出了一大堆上网的好处，而且反问我：“你不是也经常上网吗？”，于是，我产生了几个思考：告别网吧，是不是就等于告别了网络呢？告别网吧，这现实吗？我们的中学生在接触网络时，该如何把持自己呢？ 女：老师曾经说过，21世纪是知识经济的时代，是网络的时代，是人类数字化生存的时代，电脑和网络，是每一个学生都尽可能掌握的一门课程。在美国等西方国家，四五年级的学生都能够熟练地使用电脑、网络来查阅资料，学习知识。相比之下，让我们中学生告别网络的做法，我想在坐的同学没有一个会同意。 男：但我们的法律为什么又规定“禁止未成年人进入网吧” 呢？首先，我们不能把“网络”等同于“网吧”。第二，表面禁止的同时，深含对我们未成年人的身心保护。我们中

学生自制能力差，一旦迷恋网吧便不能自拔，导致学业无成，甚至是猝死网吧。这类的现象时有耳闻，如果事件发生，我们便总认为这是因无知而犯下的错误，但也为时已晚了。 女：“禁止未成年人进入网吧”是为了让我们的学生少犯或不犯相同的错误，让更多的人来关爱我们这些未成年人。 不接触网吧，我们同样可以接触网络，比如：通过家 庭的个人电脑、学校电脑室的电脑等。 男：当然，作为孩子的我，完全能够理解为什么有的人家里有电脑，但他还要去网吧。刚才也说到我们自制能 力差，只要用上电脑，便会觉得时间如白驹过隙，不 管用多久，都觉得不够。所以，每当感到刚玩了一会，就会听到父母说“你都玩了几个小时了！该去写写作业 了吧！”“你看看都几点了，还在玩？明天不用上学啊？” “你玩什么呢？这么聚精会神？要是学习也这样，还至 于几百多名吗”“你作业写完了也不能玩这么久啊！复习 去！”“作业写完了吧？来，别玩了，考考你学过的英文单 词。”“哎呀......忙了一天了，累死我了，别玩了，去把衣 服晾一下，然后扫一下地，再把碗刷了！”等。父母喋喋 不休的唠叨，真的可以让人发疯！但是大家有没有想 过，他们为什么要这样做？难道真的是因为看你不顺 眼、想拿你撒气？

中介语理论研究

中介语理论研究与第二语言教学 [摘要]中介语理论是第二语言习得研究领域中的一个认知理论。分析和研究中介语产生的根源和特点有助于了解第二语言习得机制,揭示第二语言习得的发展过程和规律。对提高教学效果有重大意义。[关键词]中介语;特点;教学 第二语言习得研究在近40年间取得了令人瞩目的成就。随着研究的不断深入和发展,人们越来越重视第二语言习得的心理过程。中介语理论把第二语言学习者的语言看作是一个内在的语言行为。因此,中介语的研究对外语教学方法论有着重要的意义。 一、中介语的概念 中介语(interlanguage)，也有人译为"过渡语"或"语际语",指的是第二语言学习者特有的一种目的语系统。是指在第二语言习得过程中,学习者通过一定的学习策略,在目的语输入的基础上所形成的一种既不同于其第一语言也不同于目的语,随着学习的进展向目的语逐渐过渡的动态的语言系统. 中介语理论认为，第二语言学习者在学习过程中所掌握和使用的目的语是一种特定的语言系统，这种语言系统在语音、词汇，语法、文化和交际等方面既不同于自己的第一语言，也不同于目的语，而是一种随着学习的进展向目的语的正确形式逐渐靠拢的动态的语言系统。由于这是一种介乎第一语言和目的语之间的语言系统，所以称之为“中介语”。 与lnterlanguage (中介语)相近的概念最早由Corder在论文《学习者错误的意义》中提出,他把学习者尚未达到的目的语语

言能力的外语能力称为过渡能力( transitional competence)。美国语言学Selinker于1969年在论文《语言迁移》中首先提出中介语假说(interlanguage)的概念。1971年,W. Nemsers在《外语学习者的相似系统》中提出了“approximative system”的概念。1972年Selinker在其著名论文《中介语》中提出的中介语假说, 对“中介语”这一概念进行较详细的阐述,是试图探索第二语言习得者在习得过程中的语言系统和习得规律的假说,在第二语言习得的研究史上有重大意义。从而确立了它在第二语言习得研究中的地位。Selinker指出:“中介语是一个独立的语言系统,它产生于学习者试图掌握第二语言所做的努力。”根据塞格林的定义,中介语既可是指第二语言学习者在学习过程中某一特定阶段中认知目标语的方式和结果的特征系统,即一种特定、具体的中介语言,也可以指反映所有学习者在第二语言习得整个过程中认知发生和发展的特征性系统,即一种普遍、抽象的中介语语言体系interlanguage continuum塞格林还指出中介语本身是一个阶段到过程的双重系统和庞大体系,即母语→中介语→目标语系统中的一个必然成分和过程。在这个系统中二语学习者从母语出发经过中介语到达目标语。并指出要到目标语必须经过中介语,中介语是第二语言认知中的必经之路。 二、中介语的产生 应用语言学领域中产生了对比分析方法(20世纪中期)。它通过对人们的母语以及所要学习的第二语言的语音、语法、词法、

英语languagepoint(完整版)

get around/round to: do (something that you have intended to do for a long time.) e.g: I was meaning to see that film but I just never got around to it. 我一直想看那部电影，但始终还是没能去看。 just as well/as well: suggesting that something will be a good thing to do/or that it was luckily that something was done or happened. 正好，幸好，不妨 e.g: “Shall I phone to remind him? ” “That would be just as well.” It was just as well you’re not here. You wouldn’t like the noise. get by (Line 3): be good enough but not very good; manage to live or do things e.g: It is a bit hard for the old couple to get by on a small amount of pension. 如果我们坚持到底，我们就能熬过难关。 We’ll get by if we hold on to the end. get across: be understood Did your speech get across to the students? get away with: run away without being punished The teller had been stealing money from the bankand got away with it. 这个出纳一直在偷银行的钱却能侥幸逃脱。 get through (Line 45): come successfully to the end e.g: We’ve stored enough food and fuel to get through the cold winter. 为了度过寒冬，我们已经储备了足够的食物和燃料。 make it (Line 9) : be successful, fulfill the purpose e.g: Having failed for thousands of times, he eventually made it. 她最后成功地成为了一家大公司的总裁。 She finally made it as a CEO of a big corporation. haul (Line 16) v. transport, as with a truck, cart, etc. e.g: These farmers haul fruits and vegetables to the market on a cart in the early morning every day. v. pull or drag sth. with effort or force e.g: A crane has to be used to haul the car out of the stream. long-overdue (Line 20) adj. Being something that should have occurred much earlier. e.g: Changes to the tax system are long overdue .She feels she’s overdue for promotion. supplement (Line 21) v. add to sth. in order to improve it (followed by with) e.g: 1) Forrest does occasional freelance to supplement his income. 2) The doctor suggested supplementing my diet with vitamins E and A. supplementary adj. additional, auxiliary spray (Line 22): v. force out liquid in small drops upon (followed by with) eg: I’ll have to spray the roses w ith insecticide to get rid of the greenfly. freelance (Line 23) adj. doing particular pieces of work for different organizations rather than working all the time for a single 自由职业者的 e.g: Most of the journalists I know are/work freelance.

Body language 课文

Yesterday, another student and I, representing our university's student association, went to the Capital International Airport to meet this year's international students. They were coming to study at Beijing University. We would take them first to their dormitories and then to the student canteen. After half an hour of waiting for their flight to arrive, I saw several young people enter the waiting area looking around curiously. I stood for a minute watching them and then went to greet them. The first person to arrive was Tony Garcia from Colombia, closely followed by Julia Smith from Britain. After I met them and then introduced them to each other, I was very surprised. Tony approached Julia, touched her shoulder and kissed her on the cheek! She stepped back appearing surprised and put up her hands, as if in defence. I guessed that there was probably a major misunderstanding. Then Akira Nagata from Japan came in smiling, together with George Cook from Canada. As they were introduced, George reached his hand out to the Japanese student. Just at that moment, however, Akira bowed so his nose touched George's moving hand. They both apologized - another cultural mistake! Ahmed Aziz, another international student, was from Jordan. When we met yesterday, he moved very close to me as I introduced myself. I moved back a bit, but he came closer to ask a question and then shook my

INTERNET演讲稿

so there are more and more people who have became internet users. do you know how many internet users in the world? let’s see the chart! 3 this is a questionnaire [?kw?st??n??r, ?kwest???ne?] (调查卷) about world internet users and population stats in 2009. the users has grown [gr?un] at a remarkable [ri?mɑ:k?bl] rate 。the rising line(上升的曲线） is not this ,not this ,is this. let us see the next pictures. 4 who is he？yes .our respectable premier [?premi?] wen .how old is he? a ha .this i dont know ,but i know he is very old , he is also surfing the internet and caring about current events and politics .so how we do ? 5 yes .the man may be watch a funny movie. the mother is telling her children learning some knowledge through the internet. in this picture .the people from different nations also learn the same thing-------how to use the internet. even the lovely dog is also want to use the internet. why are many people attracted by internet? now im not surprised to see the results, for i can find the reason just from my own life. 6 the internet changed my life; there is no doubt about that. to spend a part of our day on the internet is quite normal for many people. 7 second. the internet is a database ?deit?beis] full of latest information and offers me a lot of services. i can read the daily newspapers, movies and music from all over the world. 8 when i saw this news, my mood just like this picture—angry birds .how cruel the passed people are .ok, let me back to the topic .this is an online game--- angry birds. that’s another important part for internet .the online games are always attractive and challenging. in my opinion its more exciting to play with friends than playing alone. 9 third. to improve our english, through internet i often find professional english learning methods. is internet good or bad we should admit that there are so many advantages brought by the internet. firstly, the internet affords us lots of convenience. for example, we can shop, have meetings and even study on-line. furthermore, the internet has improved our working efficiency. we can contact colleagues on the other side of the world to talk about the working project via the internet easily. piles of files can be sent by e-mails with the help of the internet. in addition, the internet makes information conveyance much easier. just clipping “google”, related information will boom out explosively within several seconds. while applauding for those benefits the internet brings to us, we need to worry about disadvantages of the internet as well. to begin with, it is easy for the young to indulge themselves in the so-called “cyber romance”, which is full of dangers, cheatings

中介语石化现象

中介语石化现象

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