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Course: LDC 2004, Fall 2008
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This Note: document describes the transcription methods and conventions as employed by the Meeting Transcription team. Because the transcripts were later reformatted to conform to the new MRT specification, an ADDENDUM is provided at the end of the document, detailing how the markings described here were modified. Consult the ADDENDUM for the forms the user should expect to see in the MRT files. We intend to...

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This Note: document describes the transcription methods and conventions as employed by the Meeting Transcription team. Because the transcripts were later reformatted to conform to the new MRT specification, an ADDENDUM is provided at the end of the document, detailing how the markings described here were modified. Consult the ADDENDUM for the forms the user should expect to see in the MRT files. We intend to provide tools to convert between the two conventions. ====================================================================== The ICSI Meetings Corpus: Transcription Methods Jane Edwards, ICSI ---------------------------------------------------------------- 0. Overview. The Meetings Corpus transcripts are word-level transcripts, time-synchronized to digitized audio recordings. The meetings were recorded with close-talking and far-field microphones. The transcripts were based mostly on the close-talking microphones, either separately or blended together in a so-called "mixed" channel. When listened to separately, the close-talking microphones enabled detection of quiet events, and disentangling of utterances during overlaps. The mixture of close-talking microphones made it possible to to follow the flow of the conversation and hear utterances in context, with much better audio quality than would have been possible from far-field microphones. Far-field microphones were used either when a speaker was not wearing a microphone (e.g., during meeting set-up), or when a microphone malfunctioned. Transcripts were prepared by means of the "Channeltrans" interface (http://www.icsi.berkeley.edu/Speech/mr/channeltrans.html). Channeltrans is an extension of the "Transcriber" interface (Barras, Geoffrois, Wu, and Liberman, 2000), modified by David Gelbart and Dan Ellis to accommodate multiple speakers, and overlapping speech. Both Transcriber and Channeltrans preserve events and time bins in which they occurred, and both of them do so in XML format. Channeltrans differs from Transcriber in that it preserves the channel number in addition to the time and event. Whereas Transcriber has only one display ribbon for speaker utterances, Channeltrans affords as many display ribbons as there are speakers. Furthermore, Channeltrans allows the time bins on each ribbon to be totally independent of those on all other ribbons. Both properties -- multiple ribbons and independent time segmentation -- were essential for the Meetings Corpus data, due to the large number of participants and great amount of overlapping speech in these meetings. The basic strategy of the transcript was to view each ribbon as capturing the actions of a particular meeting participant, heard over the close-talking microphone which he or she was wearing. The person wearing a particular microphone is called the "dominant" speaker on that channel. In cases of crosstalk, other speakers may be heard on the same channel, but only the events produced by the dominant speaker are transcribed on the display ribbon corresponding to that channel. Expressed another way, no event is transcribed more than once, or attributed to any channel other than the channel on which the speaker is the dominant speaker. The most basic unit of analysis in these transcripts is an event, the time bin containing it, and the person who produced it. The time bins are only practical units rather than theory-relevant units. The goal was simply to have units of manageable size with no truncated words. Thus, an utterance can extend into subsequent time bins, so long as there are clean breaks between them. To speed the transcription process, a speech-nonspeech detector was used to provide a preliminary segmentation of the data into time bins. Although the time bin boundaries were not always accurate, it was still more efficient than having transcribers add all boundaries themselves. This process is explained in greater detail in section 3 below. After the transcripts were completed, they were checked, first by other transcribers, and then by one of two senior researchers. The details of the checking procedures are described in section 4 below. After the transcripts were completed and checked, some of the surface labels below were converted by scripts into XML tags (see Addendum). It's important to note that this is a difference only of the surface-level graphemes; not the distinctions which are encoded in the transcripts. This difference has been expressed elsewhere as one of "markup" versus content (see Edwards, 1995, p. 20). The distinctions described below are the meanings captured in the Meetings Corpus, regardless of which surface graphemes are used to display them in the markup. This document describes the specific content distinctions which were encoded in the transcripts. Section 1 describes the transcription conventions which were used for all interactional parts of the meetings (i.e., all but the Digits task). Section 2 indicates how these conventions were applied to the Digits task. Section 3 presents the details of implementing the transcription conventions, esp. with reference to Channeltrans and the speech-nonspeech presegmenter. Finally, Section 4 describes the steps and processes used in checking the transcripts before considering the transcription encoding phase complete. 1. Transcription Conventions (except for the Digits task, which is discussed in section 2) The transcription conventions used in this project were shaped by two sets of factors. The first set was the intended audience: primarily speech recognition research, and secondarily linguistic and discourse research. The former audience requires matching of word forms against lexical entries. The latter requires preserving communicative events. The second set of factors were practical considerations: speed of data entry, robustness against human error, and computational utility. These interests are shared by all well-designed transcription systems. Some of the strategies used include: minimalism (using as few separate symbols and as few interpretive decisions as possible), use of familiar literary conventions where possible (e.g., a dash for incompletion), use of conventions which are reasonably transparent through other motivations where that's not possible, etc. (See Edwards, 2002 for a more comprehensive list). The focus of the transcripts was on capturing the flow of audible events, especially the words which were spoken, and who spoke them. The basic unit of analysis was an event, the time bin in which it was located, and where relevant or possible, which participant produced it. There are five types of "events" in these transcripts: 1) Words 2) Utterances 3) Vocalizations which are not words - e.g., laughs, coughs, breaths 4) Nonvocalized sounds - e.g., door slams, microphone noises, chair squeaks 5) Silence With words, utterances and other vocalizations, it was almost always possible to determine the relevant actor by comparing loudness across different close-talking microphones, or by noticing distinctive characteristics of voice or accent. Non-vocalized sounds, such as doors slamming or chairs squeaking, were attributed to individuals in the transcripts when this was obvious from context or from comments from participants (e.g., when someone's microphone suddenly becomes active, or when someone teases the person for being late). Where it was not clear who produced them, the noises were simply noted as occurring, without attribution. Silence was the absence of events of the other four types. Some speakers were silent for long stretches during a meeting. This type of silence was routinely encoded. When a silence occurred within an utterance it was sometimes encoded but not exhaustively so, and similarly, for when breath occurred within an utterance. In addition to the five event types, the transcripts contain additional clarifying information or "metacomments," typically expressed inside curly brackets with a "QUAL" label inside the opening bracket. These comments include such things as contextual notes, and observations concerning acoustic or discourse features. The transcripts also contain some types of information which can be derived indirectly from the representation rather than being explicitly encoded. A primary example of this is overlapping events, which can be defined with reference to time tags on two different speaker channels. Sections 1.1 through 1.5 provide details of the five event types. Section 1.6 explains the encoding of metacomments. Section 1.7 discusses the relative exhaustiveness of encoding of the various types of distinctions in the discourse section of the meetings. 1.1. Words All word-level transcription followed the same rules: - encode words in standard orthography, - indicate uncertainty of transcription where it exists. Under no circumstances was "word salad" allowed, i.e., transcribing a string of words which sounds somewhat like the speaker's utterance, but which was most certainly wrong or made no sense in context. Where uncertainty arose, parentheses were used, and one of the following encodings was used inside the parentheses: - If the transcriber was reasonably sure of a word or phrase (and it made sense in context), the uncertain word or phrase was enclosed in parentheses: (word or phrase) - If the transcriber was not sure of a word or phrase, but was fairly certain that it was n syllables long, the number of syllables was followed by an "x": (nx) - If the stretch of speech was totally undecipherable and contained an indeterminate number of syllables: (??) There are several types of "words" in the transcripts: a. Standard word forms found in the dictionary. These are encoded in standard orthography. Hyphens are used to bind together the parts of a lexical compound, as in standard orthography. Hyphens are also used to bind together components of some frequently occurring technical terms (e.g., speech-nonspeech detector). b. Truncated words. These are words whose articulation is stopped by the speaker before they are completed. This is encoded by means of a hyphen appended to the end of whatever was articulated. For example: th- c. Numbers, decimals and percentages. These are spelled out in standard orthography (e.g., "five point two", "twenty-five"). d. Pronounceable acronyms (e.g., "UNESCO", "ChiLDES") are encoded with the same capitalization patterns as are usually used for them in writing. e. Spoken letters are encoded as capital letters followed by underscores (_). When they occur individually there is an underscore after each spoken letter. - discussion points: "So the news for me is A_, my forthcoming travel plans in two weeks." - variable names: "the log of X_ plus N_" "That might, you know, give us additional input to belief A_ versus B_." When they occur in clusters, there is an underscore (and no space) after each letter except the last one: - acronyms pronounced as a string of letters: "I_C_S_I" (Acronyms which are pronounced as words rather than strings of letters are encoded with no underscores, e.g., "ICSI" when pronounced like "icksy".) - spellings: "His name is Hudson, H_U_D_S_O_N." When they are a part of a technical term, there is always an underscore after the letter. The separate parts of the term are bound together by the underscore alone or by an underscore plus a hyphen or by a hyphen, depending on whether the letter precedes or follows the non-letter part of the term, or, when there are two letters, depending on what would seem the most easily readable encoding: - technical terms: - letter followed by non-letter segment: "This is a plot of C_zero, the energy." - non-letter segment followed by letter: "What you're saying is we have a Where-X_ question." - two letters and a non-letter segment: "M_-three-L_ enhancement" In this corpus, underscores occur only in the context of spoken letters. f. Word forms typical of spoken discourse, which may be absent from a dictionary (e.g., reduced forms such as "gonna" and "cuz", backchannels such as "mm-hmm", interjections such as "oops!"), but which often have a conventionalized spelling in literature. These are encoded using the shortest list of forms which capture meaning differences but avoid needless proliferation. (For example, "uh-huh" is always encoded as "uh-huh"; if it is lengthened, the lengthening is treated as being an embellishment and is handled by a comment immediately following the word or utterance.) g. "Vocal gestures". These are less word-like vocalizations which, however, are communicative (rather than being reflexive behavior). For example, "pppt!" which is sometimes used to signal an easy task, or "hhh" which stands for a vocalized outbreath of frustration or difficulty. h. Departures from canonical pronunciation: the "PRN" tag. This category was motivated by the goal of advancing speech recognition research, to indicate pronunciations which are noticeably different from the pronunciation variants which would normally be expected of the speaker who uttered it. PRN items are recognizable by humans, but are perceived by human transcribers as being beyond the range of normal pronunciation variation, such that non-humans could be expected to find them more difficult to recognize than usual. Items which are tagged PRNs include: - words which have been extremely lengthened (i.e., seeming subjectively to be probably several standard deviations beyond normal length for that speaker) - words which contain rare acoustic artifacts which might affect the waveforms (e.g., an initial vocal squeak, or a crack in the voice) - non-words which arise from speech errors of some types but which sound prosodically complete Items which are NOT tagged as PRNs: - prosodically incomplete words/nonwords (already handled via the truncation convention above, using the end-hyphen) - words which are tinged by a non-native speaker's mother tongue (since these pronunciations would be part of an accurate model of that person's variety of English). That is, if the person is a native Spanish speaker and says what sounds like "Espain" instead of "Spain", the word is simply transcribed as "Spain" without special marking. The following is an example of PRN marking: 'O_K. {PRN "mm-kay"} PRN marking has these parts: - an apostrophe (') pre-pended to the beginning of the non-canonical stretch (which may be one or more words in length), - the word(s) in the non-canonical stretch, spelled in standard orthography, (O_K). - a PRN tag after the stretch, and - an optional rendering of the speaker's pronunciation, or a description of how it is different from canonical pronunciation (in this example, "mm-kay"). The following illustrate some other types of PRN marking: 'folks. {PRN "folksss"} 'She {PRN lengthened} 'this could {PRN "thisss kid"} The description field is usually empty for speech errors because they are accidental productions which should not normally be viewed as intended renderings of a word in the language (and hence would not be normally added to a model). Lengthening (and other embellishments) which are within the normal range of pronunciation variation are normally noted in QUAL comments (discussed later in this document) instead of PRN comments. i. Foreign words and phrases. These are encoded in a manner similar to non-canonical pronunciations (section h), except with a language abbreviation in place of "PRN" (e.g., GER for German). A recognizer trained on English would not be expected to have them in its lexicon or language model. Tagging them makes it possible to exclude them from some experiments if desired. 'ist fertig. {GER "is finished"} 'oder {GER "or"} 'Nein! {GER} 'cum grano salis. {LATIN meaning "with a grain of salt"} 'en passant, {FRENCH "in passing"} 'Bien sur {FRENCH meaning "of course"} 'pero {SPAN meaning "but"} 'tango de la muerte. {SPAN} 1.2. Utterances A discourse consists of units of various sizes. For purposes of this document, "utterances" are stretches of words which begin with a capital letter and end with a punctuation mark and/or a comment in curly brackets. Punctuation marks signal two types of information: whether an utterance is complete or not and what type of utterance it is: - Exclamations end with exclamation point (!). - Statements end with a period (.) unless they are intended as questions. - Utterances with the pragmatic force of questions end with a question mark (?). (This includes some statements spoken with rising intonation, but not explanations spoken with rising intonation, in which case, the rising intonation serves to elicit listener feedback, rather than to signal a propositional question.) - Disfluencies and incomplete utterances end with a space and a hyphen unless their last word is truncated, in which case they end with simply the hyphen attached to the truncated word (section 1.1.b). The following example contains only completed words: I was - these meetings - I'm sure someone thought of this, but these - This example has a truncated word (and thus has a hyphen appended to it): It'd be nice, but - but I - I - I do- I don't wanna count on it. If the utterance was clearly a question, the hyphen can be followed by a space and a question mark (- ?). For example: So, uh, what was the date there? Monday or - ? The "- ?" notation is used only when there is no doubt that the utterance was intended by the speaker as a question (e.g., due to a combination of syntactic factors, prosody, response from seeming addressee, etc.). Only very few truncated utterances are marked as being truncated questions in the interests of staying close to the actual data rather than guessing what the person might have intended or said if he or she had continued speaking. The end-punctuation marks in this corpus were based considerably less on prosodic distinctions than is true of many discourse corpora. This approach was chosen with the intention of providing the primary audience (speech researchers) with the types of distinctions of greatest use to their research. Some prosodic information is preserved by two other mechanisms: - asterisk (*) for marking prosodic prominence: "So it's not really - you're not really *exposed to German very much." - QUAL comments for describing various properties of the utterance which precedes the comment: "We use a generalization of the - the SPHERE format. rising {QUAL intonation}" This particular utterance was a statement of clarification by the speaker, with rising intonation to get feedback from the listener. The utterance would have had a very different meaning (and been pragmatically bizarre in the context in which it arose) if it had been encoded as a syntactic question, i.e., punctuated with a question mark. Neither stress nor intonation is exhaustively coded in the corpus. They are added mainly as points of enticement for future work. Other punctuation in this corpus: - comma (,), used in a manner similar to written orthographic standards, - double quotation mark ("), used to encode any material which is being quoted by the speaker. The literary convention of encoding embedded quotes in single quotes (') is avoided to avoid confusions with PRN items. (See section 1.1 above.) Instead, embedded quotations are marked by double quotation marks (") as are un-embedded quotations. This can give rise to some rare ambiguities of scope, where it is not clear where the embedded quote ends within a quoted stretch. But there are only a handful of cases in the entire corpus which have embedded quotes, so it was not considered an abundant enough event to require an extra convention. It is illegal to have a space in front of the following markers: period, comma, exclamation point, utterance-final quotation marks. It is illegal to have a space immediately after this marker: asterisk. The ordering of punctuation marks is roughly that of standard orthography, with one exception: commas and periods can be placed outside of the final double quotation mark if it is notionally justified, for example, if the speaker is quoting a term within an utterance. Thus: The term to use there is "temporary". Colons and semicolons are not allowed in the corpus. If an utterance would most naturally be rendered with a colon in written orthography, a comment containing the word "colon" is sometimes put immediately at that point in the utterance (to enable a shift in conventions later on if that distinction becomes important to preserve). 1.3. Vocalizations other than words When the speaker is not speaking, he or she sometimes produces other vocal sounds, including such things as "laugh", "cough", "breath", etc. These are set apart from the utterance, and tagged as so-called "VOC" events. They are enclosed in curly brackets after an initial "VOC" tag. When a laugh or cough, etc. occurs *during* the articulation of a word, it is viewed not as a VOC, but rather as a modification of on-going articulation, and is instead tagged as a "QUAL" (i.e., "qualification" comment) event. (QUALs are described in a later section, below.) There are far too many types of VOCs to discuss them all separately, but a couple of them warrant some comments. The VOC descriptors "laugh-breath" or "breath-laugh" were intended initially to signal an event which was ambiguous between a laugh and a breath. It has become generalized to also capture some events which are clearly laughs but lack voicing, such as events which are identifiable from quick rhythmic breathiness and context. The VOCs "inbreath" and "outbreath" are more specific than "breath" but these distinctions are not exhaustively encoded. If two VOC events occur in succession, they are generally mentioned in separate bracketed comments (to keep the list of VOCs as short as possible). 1.4. Nonvocalized sounds These include "door slam", "microphone noise", "chair squeaks", etc. They are enclosed in curly brackets after an initial "NVC" tag. Many of them are audible across more than one channel. Some of them are attributable to individual speakers but many are not. If two NVC events occur in succession, they are generally mentioned in separate bracketed comments (to keep the list of NVCs as short as possible). 1.5. Silence Double periods without space between them (..) means silence. 1.6. Clarifying information There are several types of clarifying information in the corpus. 1) punctuation (discussed in section 1.2 above) 2) metacomments expressed in curly brackets with an explicit tag indicating the type of information they encode. Two types of metacomments were discussed in section 1.1 above: those for non-canonical pronunciations (PRN) and those for non-English expressions (GER, etc.). The main type of metacomment in the data is the QUAL comment. It is used for comments concerning such things as likely referent, likely addressee, or various possibly interesting discourse factors such as voice quality. It is also used to note modifications of articulation (e.g., lengthening) or to capture simultaneity of events ("during microphone spike" or "while laughing"), and so forth. Speaker identifiers may appear in comments which indicate the intended addressee for an utterance or which clarify ambiguous references or describe ongoing actions, but these are relatively rare. The primary mechanism for attributing acts to individual participants is the XML "channel" tags. In the original transcripts, QUAL comments were encoded in curly brackets beginning with a "QUAL" tag. All QUAL comments are positioned either at the point of relevance or immediately after the segment or unit to which they apply most clearly; not before it. In the event of an interrupted utterance, the PRN precedes the space and hyphen, whereas the QUAL follows it. The reason for this is a difference of scope for their most typical instantiations. That is, PRN is usually word-level in what it clarifies (and less often applies to phrases) whereas QUAL is usually phrase level (and less often applies to individual words). The contents of a QUAL were kept as short as possible, and were kept to as short a list as possible by using the same wording across meetings as much as possible. Thus, "again" was avoided on subsequent occurrence of an event. QUALs containing multiple parts were split into two adjacent comments where this would lead to a shorter total list of them in the corpus (i.e., avoiding compounding in the same way as discussed for VOCs and NVCs above). 1.6.1. The scope of clarifying information Comments which refer to a word or utterance are placed immediately after the word or utterance they refer to, and in the same time bin. For example: It's mine! All mine! {QUAL while laughing} The comment refers to all or part of the preceding utterance. In the interests of time, the exact scope was usually not specified, though sometimes it was: which I'm not gonna have time to do in the next few days, {QUAL last 5 words spoken while laughing} The goal was to indicate the occurrence of something interesting in a time bin in the most efficient and least time-consuming way. In some cases, a comment contains background information which may be relevant not only to the preceding utterance but also to utterances which follow it. For example: Speaker B: I was just gonna say maybe fifteen minutes later would help me a little bit just cuz I have a class up at Dwinelle b- just before this. That's why I was a little late today because - Speaker A: *Wow. You did really *well. {QUAL addressee recently had knee surgery} Speaker B: Thanks. {VOC laugh} Well, I took the bus for part of the way. But um, that might help me just a *little bit because then it - I - you know, I'm gonna - gonna be hobbling a little slowly. It is often impossible to determine the point at which such a state of the world becomes relevant or irrelevant to the unfolding interaction. For this reason, in the present conventions, as in most discourse transcription conventions, it is desirable to insert comments where they are known to be relevant but to avoid giving an explicit end-point to their relevance to the discourse, as this is ultimately unknowable, often even to the participants themselves. (See Edwards, 1993, pp. 17-18 for contrasting approaches to scope.) 1.7. Exhaustiveness of the encoding It's useful to mention the priorities of transcription for this project, as a guide to what phenomena were most robustly and exhaustively encoded. The most robust parts of the corpus are: - "words" in the technical sense of strings of one or more characters representing phonations by the speaker. This includes all of the categories and subcategories of section 1.1. - speaker attribution for the words. That is, correctly attributing articulations to the person who actually uttered them rather than to another speaker. - encoding of communicatively salient vocal (VOC) events - esp. "laugh" - encoding of loud reflexive VOC events - esp. "cough", "sneeze", and to a lesser degree (because these were less audible, and easier to overlook) "sniff" - encoding of loud nonvocal (NVC) events - esp. door slams - encoding of certain types of QUAL comments - esp. "while laughing" because it is the most common speech embellishment in the data, because it is communicatively significant, and because it may hinder word recognition by human and machine. Reasonably robust but somewhat less exhaustive/consistent: - events which occurred too often to be exhaustively marked within the parameters of this project: microphone spikes, breaths. Some meetings contain more exhaustive encoding of breaths than others. - events which were less audible (lower volume): some backchannels or sniffs. Many of these were overlooked entirely by the automatic presegmenter and were added manually by transcribers or by data checkers. It is inevitable that some were overlooked, esp. the unusual category of backchannels which were of such low volume that they were not even audible to others at the meeting. - the punctuation at the ends of utterances. The goal was to provide a useful and reasonably consistent set of markers, and this was accomplished. Punctuation was double-checked or even triple-checked by different transcribers, but there is more chance of variability in this part of the corpus than in the parts noted above. Sporadically encoded curiosities for future work: This third category contains a variety of phenomena which caught the transcribers' or data checkers' attention as interesting and worth preserving, but which were not part of the main goals of the project. This includes: rare events, curiosities and ideal examples of particular phenomena. "Rare events" are such things as extremely long silence across all channels (as in Bro005): {QUAL very long silence, 11 seconds} Under "curiosities", there are glottal clicks, and unusually high whistles produced by a talented linguist in Bsr001. Under "ideal examples" is the remarkably tight rhythmic coordination of backchannels across 5 speakers at several points in Btr002. These and similar things were encoded in the corpus to provide a sense of the richness of the data and a glimpse of what other types of phenomena a person might study in this corpus which go beyond the scope of basic transcription. 2. Conventions used for the Digits task The "Digits" task involved reading strings of one or more digits from lines of printed scripts. Not every meeting contained this task, but where it occurred, they were transcribed as follows: - Every event was transcribed: from the r...

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Ling 001: Syntax IIMovement & Constraints 2-11-2009Phrases In the last lecture, we talked about simple phrases; e.g. Noun Phrases like The dog The big dog The big dog that John was talking to In this lecture, we will look at how phrases and
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GenieandLanguageAcquisitionHowchildrenlearntospeakandwhat happensoncetheypassthecritical periodwithouthavingdoneso.Infants:010mos. Infantscandistinguishsoundsfrombirth,even ifthosesoundsarenotpartoftheirparents speech. Bysixmonths,babiesbegintol
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LanguageContactpresentedby MichaelL.Friesner August6,2007Thank you to Gillian Sankoff for sending me her PPT slides (among other things).TwoMainTypesof LanguageContactAgent:Nonnativespeakersaffectingalanguagethey cometospeak languageshift
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Acts of Conflicting IdentityThe Sociolinguistics of British pop-song pronunciation by Peter TrudgillThe Accent of pop singing At least since the 20s and the advent of Jazz, singers have adopted speech patterns while singing that are different fro
UPenn - LING - 001
A puzzle: why language? Quantitatively and qualitatively unique like elephants trunks No similar evolutionary trends in other species other species dont want to pick up peanuts with their noses all mammals have flexible noses, some use them as
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LING 120 Introduction to Speech AnalysisFall 2007Week 6Speech analysis II: Stops, nasals, liquidsOct. 8-12, 20072LING 120 Introduction to Speech Analysis, Fall 20073LING 120 Introduction to Speech Analysis, Fall 20074LING 1
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LING 520 Introduction to Phonetics IFall 2008Week 9Basic audition Speech perception Nov. 3, 20082LING 520 Introduction to Phonetics I, Fall 20083LING 520 Introduction to Phonetics I, Fall 20084LING 520 Introduction to Phonetics
UPenn - LING - 520
LING 520 Introduction to Phonetics IFall 2008Week 2English consonants and vowels Articulatory phonology Sep. 15, 20082 1. Consonants are longer when at the end of a phrase (bib, did, don, nod). 2. Voiceless stops (i.e., /p, t, k/) are asp
UPenn - COGSCI - 501
Loudness predicts prominence: fundamental frequency lends little.G. Kochanski and E. Grabe and J. Coleman and B. Rosner( 2006/08/27 09:49:02 UTC )Running title: Fundamental Frequency Lends Little Prominence The University of Oxford Phonetics Lab
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Psychological Review Vol. 65, No. 6, 19S8THE PERCEPTRON: A PROBABILISTIC MODEL FOR INFORMATION STORAGE AND ORGANIZATION IN THE BRAIN 1F. ROSENBLATT Cornell Aeronautical LaboratoryIf we are eventually to understand the capability of higher organi
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LING 120 Introduction to Speech AnalysisFall 2007Week 5Speech analysis I: Vowels and FricativesOct. 1-5, 20072[From: UCL phonetics website]LING 120 Introduction to Speech Analysis, Fall 20073LING 120 Introduction to Speech Ana
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LING 520 Introduction to Phonetics IFall 2008Week 3Sounds in other languagesSep. 22, 2008Languages in the world There are about 7,000 languages in the world today. Over half of them (52 percent) are spoken by fewer than 10,000 people; over
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268IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,VOL. 24, NO. 2,FEBRUARY 2002Short Papers_Two Variations on Fishers Linear Discriminant for Pattern RecognitionTristrom CookeAbstractDiscriminants are often used in patter
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Right Linear GrammarsLing 106 October 8, 20031.Regular languages as languages generated by FSAWhen we did distributional analysis, we saw that linguistic units in natural language (roughly words) can be classified into grammatical categories o
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LING 520 Introduction to Phonetics IFall 2008Week 5Acoustic theory of speech production Acoustics of vowels Oct. 6, 20082 LING 120 Introduction to Phonetics I, Fall 20083LING 120 Introduction to Phonetics I, Fall 20084n=2L
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LING 120 Introduction to Speech AnalysisFall 2007Week 2Anatomy of speech production Phonetic transcription RecordingSep. 10-14, 20072Nasal Cavity Oral Cavity Pharynx Larynx: vocal folds in it Trachea: the windpipe Lung: supply airstreamSa
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LING 120 Introduction to Speech AnalysisFall 2007Week 4Acoustics of speech production SamplingSep. 24-28, 20072 LING 120 Introduction to Speech Analysis, Fall 20073n=2L nfn =vn=nv 2Ln = 1, 2, 3.L = /2 = 2L f = v/
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LING 120 Introduction to Speech AnalysisFall 2007Week 3Physics of soundSep. 17-21, 20072Motion: Distance (unit: meters, 1 m 39 inches); displacement (vector); Speed = distance / time (units: meters/sec, m/s); Velocity specifies the di
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LING 120 Introduction to Speech AnalysisFall 2007Week 8Speech analysis IV: Variation and statistical techniques (I)Oct. 22-24, 2007Variation in speech2 Linguistic factors: phonetic context, intonation, syntax/semantics, etc. Paralin
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LING 120 Introduction to Speech AnalysisFall 2007Week 9Speech analysis IV: Variation and statistical techniques (II)Oct. 29 - Nov. 2, 2007Hypothesis testing Steps for Hypothesis Testing: 1. Formulate your hypotheses: - Need a Null Hypothesis
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LING-102, Summer 2007Instructor: Marjorie PakJuly 25, 2007Homework 4. Due Monday, July 30, at 10am. Part of the homework will be handwritten and turned in to me in class; the other part will be emailed to me before class. See below for exact in
UPenn - LING - 120
LING 120 Introduction to Speech AnalysisFall 2007Week 1Overview of the course The speech chain Linguistic organizationSep. 5-7, 2007Syllabus2http:/www.ling.upenn.edu/courses/ling120/LING 120 Introduction to Speech Analysis, Fall 2007
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LING-102, Summer 2007Instructor: Marjorie PakHomework 2. Due Wednesday, July 18, at the beginning of class. 1. The following spectrogram shows me saying two separate made-up words with a pause in between. Each word is composed of three vowels. On
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Signal Processing ToolboxFor Use with MATLABComputation Visualization ProgrammingUsers GuideVersion 4.2How to Contact The MathWorks:PHONEFAX MAIL508-647-7000 508-647-7001Phone Fax MailuINTERNETThe MathWorks, Inc. 24 Prime Park
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LING 120 Introduction to Speech AnalysisFall 2007Week 7Speech analysis III: Speech prosodyOct. 17-19, 20072LING 120 Introduction to Speech Analysis, Fall 20073LING 120 Introduction to Speech Analysis, Fall 20074Tone1: High level
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LING-102, Summer 2007 Homework 1. Due Wednesday, July 11 at the beginning of class (hard copy) Part 1. Pick any sentence from todays class handout that contains at least 5 words, and transcribe it on a separate piece of paper using the IPA. Bring you
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SyntaxLING 001 - October 11, 2006 Joshua TaubererSyntaxHow can the words of a language be put together?SyntaxWhat makes a valid combination or order of words? What are the relations between the words in a sentence? What is the mecha
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Sound StructurePart II: Phonology 1-28-2009Review of Phonetics Speech sounds are decomposable into articulatory primitives (also known as features) Consonants and Vowels Feature differences (e.g., voiced vs. voiceless, nasal vs. not nasal, labi
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undergraduate faculty campus student college academic curriculum freshman classroom professor moral considerateness bison whale governance utilitarianism ethic entity preference utilitarian diabetes elderly appendix geriatric directory hospice arthri
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Semanticsand some syntax, math, and computational linguistics tooLING 001 - October 16, 2006Joshua TaubererSemantics Why does a sentence mean what it means? What are the meanings of words and how do they come together to make larger meanings
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Linguistics 001: StructuresSyntax I 2-9-2009Plagiarism at Harvard Last year, a Harvard student accused of plagiarism of a teen novel Sabrina was the brainy Angel. Yet another example of how every girl had to be one or the other: Pretty or smart
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Who has a more sophisticated communication system, molluscs or monkeys? frequency and length of communicative interactions? role of communication in social life? number of distinct communicative displays? information content (entropy) of communi
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featuresofAAVEasfeaturesofPPE:a studyofadolescentsinphiladelphiapaperby: tonyawolford keelanevanini presentationby: anthonysobackground puertoricansfoundtoadoptaspectsof AAE effectsofdirectcontactwithAAE grammaticaluninflectedbe phonologica
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LING 521 Phonetics PracticumLiberman & Yuan, Spring 2006Lecture8IntroductorystatisticsIII: Correlationandregression MoreonANOVA Mar.1,2006Correlation Istherearelationshipbetweentwovariables(e.g.,ageand speechrate)?Whatisthestrengthofthisrelati
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LING 521 Phonetics PracticumLiberman & Yuan, Spring 2006Lecture7IntroductorystatisticsII: ttests OnewayANOVA Feb.22,2006Review:distributionofsamplemean Themeanofthesamplemean(X)isthepopulationmean(): mean(X)=Overrepeatedsamples,thesamplemeanw
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LING 521 Phonetics PracticumLiberman & Yuan, Spring 2006Lecture5Probability Machinelearning (ataglance) Feb.8,2006Probability Itisatruthvaluethatallowsyoutobeuncertain,ifyouwish. Itdescribeshowmuchyouknowaboutasituation. Itcountshowbigaspec
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LING 521 Phonetics PracticumLiberman & Yuan, Spring 2006Lecture6IntroductorystatisticsI: ExploratoryDataAnalysis Inferenceofpopulationmeans Feb.17,2006Fundamentalconcepts Statistics:thescienceofcollecting,analyzing,andinterpreting data. Popula
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undergraduate faculty campus student college academic curriculum freshman classroom professor moral considerateness bison whale governance utilitarianism ethic entity preference utilitarian diabetes elderly appendix geriatric directory hospice arthri
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Linguistics 001Spring 2009Professors David Embick and Charles YangBasics An introduction to the scientific study of language No prerequisites Satisfies Gen.Req. V/Sector VIIWebpage Information about readings and other matters will appear on
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LING-102, Summer 2007Instructor: Marjorie PakJuly 25, 2007Homework 4. Due Monday, July 30, at 10am. Part of the homework will be handwritten and turned in to me in class; the other part will be emailed to me before class. See below for exact in