Abstract
We present and describe the Italian Roots in Australian Soil (IRIAS) speech corpus. Following a sociophonetic approach, our aim is to extend and complement the frequently investigated macro-structures of lexical, syntactic and morphological interactions among immigrants’ languages and common sociolinguistic investigations about immigrants’ language attitudes. We first discuss and motivate the creation of the IRIAS corpus. We then focus on the specific methodological issues we addressed in compiling a corpus of natural spontaneous speech collected in Veneto or Calabrese dialects, Italian and English from first and second generation Italo-Australian speakers originating from two specific regions in Italy (Veneto and Calabria). A detailed description of the IRIAS corpus follows, including its design, collection procedure and processing. The latter focuses on novel manual and automatic solutions we implemented to overcome the challenging dearth of existing resources. These solutions help advance work on spontaneous speech data. We conclude by providing some insights on what has been achieved thus far as well as the analyses currently being carried out on subsets of the IRIAS corpus.
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Notes
Indeed, according to the last comprehensive census (Australian Bureau of Statistics, ABS, 2016), about one (1) million members of the Australian population listed Italian ancestry, with at least one or both parents born in Italy or in Australia. More specifically, within Greater Sydney (Greater Capital City Statistical Areas), the 2016 census (ABS, 2016) reports that 40,497 people were born in Italy, 31.8% of whom arrived in Australia from 1951 to 1960 and 33.4% between 1961 and 1970 (in the 2011 census, these same figures where respectively 41,784, 35.8% and 34.8%).
In Italy, the standard/dialect diglossic relation dramatically changed after WWII. Due to the rising level of education, the internal migration and the spread of television, Italian became the language used by the majority of the population (De Mauro et al., 1993), creating the premises for the birth of the first generation of native speakers of the national language.
As reported by Rando (1990) about the presence of Italians from various communities in Italy in Australian metropolitan areas during the Post World War I period, “there are areas such as Sydney’s inner west and Melbourne’s northern suburbs where there is a distinct Italian presence, often characterized by Italian spoken in the streets, shop signs and advertising material in Italian” where “Language […] seems to be an important factor in the definition of community” and where “First generation Italian speakers show considerable language loyalty […]” (Rando, 1990, p. 9). However, observations have also shown that the migratory movement to rural areas of Australia, in particular, has more often followed the pattern of a “chain” migration, which created “districts in which emigrants are bound together by shared kinship ties based on a specific village” (Tosi, 1991, p. 337). In other words, Italians from a given town or region settled in specific towns in more rural Australia creating regional nuclei of linguistically homogeneous communities such as, for example, the town of Griffith, in New South Wales, where more than 60% of the population is Italian (or of Italian descent). Among them, more than half originated from Veneto, mostly from Verona. In the 1950s, when the Veneti accounted for 75% of Griffith’s Italian residents, there was little need for them to learn either English or the dialects from other regions of Italy (Corazza et al., 2012), nor indeed to learn standard Italian per se.
When those migrants embarked on the ships that brought them to the “other side of the world”, very few of them had learned the language of their future land. The vast majority of them acquired it only by immersion once in Australia.
While we collected the corpus aiming at a micro-linguistic analysis of a set of specific phonetic properties that characterize the speakers’ dialects and the changes they might undergo due to the contact with the other varieties of the speakers’ repertoires, within and across generations, other macro-sociolinguistic analyses are possible once all the recorded data become fully searchable. These include, for example, the study of code-switching, code mixing and lexical borrowings, made possible by focusing on spontaneous narratives elicited through dialogues with the interviewers.
Nagy’s corpus includes also Faetar, an endangered Francoprovençal dialect spoken in Apulia, Italy, as a minority language.
Note that /d/ gets lenited to [ð̞] in intervocalic position in both NeVen and CVen systems.
This absence is explained by the diachronic development of the phonology of Italo-Romance dialects from Latin (for a more in-depth discussion the reader is referred to Maiden & Parry, 1997; Tekavčić, 1972). In general, palatalization of Latin /k/ became the voiceless apical affricate /ʦ/ (with further developments) in Northern Italian dialects, including Veneto, and palatal affricate /ʧ/ in the Central and Southern ones. As for Latin /g/, it became the voiced affricate /ʣ/ (with further developments) in Northern Italian dialects, affricate /ʤ/ in Tuscany and Central Italian dialects, and the voiced palatal fricative /ʝ/ in most of Southern dialects (see Tekavčić, 1972: 187ff for a detailed discussion). In both systems Latin /k, t/+/l/ clusters evolved into the voiceless affricate /ʧ/.
According to the Australian Bureau of Statistics 2011 census (ABS, 2011), out of the population born in Italy who live in Greater Sydney (Greater Capital City Statistical Areas), 56.0% were aged 65 years and over, with a median age of people in Greater Sydney of 67 years.
It is important to note that in both atlases the authors based their enquiries and observations for each point under investigation on a very few speakers (in most cases just one speaker) and few tokens per word (usually just one). This is standard for language atlases.
For Veneto speakers, audio excerpts were extracted from the Atlante Multimediale dei Dialetti Veneti (AMDV) with the kind permission of its author (Tisato et al., 2013). For speakers from Calabria this step was achieved directly by the first author who has spoken Calabrian dialect since childhood. He conversed with Calabrian participants in their dialect from the very beginning even before starting the interview.
For overall consistency in this paper, the questions that follow are labelled following the file name coding rules (e.g. as q01, q02, etc.) that are separately described in more detail in Sect. 4.5.
In the very first interviews we carried out, we started by asking three separate questions, one for each language (e.g. dialect, Italian and English) which we later decided to merge and combine into a single question. For this reason in the corpus there may be questions labelled as q08 and q09, as well, which at a certain point we did not use with later participants, but these codes were left unchanged for internal consistency in our filename coding protocol. This also explains why we jump in this numbered list from q07 to q10.
The transcription guidelines, version as of February 2011, are available at: https://www.ling.upenn.edu/~wlabov/L560/Transcription_guidelines_FAAV.pdf, page last accessed July 23, 2018.
Version 1.5.0.1 (2016-04-03); https://github.com/readbeyond/aeneas.
The need for Italian language support a-priori excluded FAVE-align (Forced Alignment & Vowel Extraction developed by Rosenfelder et al., (2011) and based on the Penn Phonetics Lab Forced Aligner or P2FA); Prosodylab-Aligner (Gorman et al., 2011) which evolved into the Montreal Forced Aligner (McAuliffe et al., 2017).
https://clarin.phonetik.uni-muenchen.de/BASWebServices/interface/ChunkPreparation, page last accessed September 23, 2019.
The transcription corresponds to the phonological transcription of each language (Italian or English, Australian English in our case) which we processed separately. Dialectal speech was also processed using the Italian language model providing us a raw time-aligned phonetic segmentation and labelling that we later were able to refine and manually check and update.
For more details see http://alveo.edu.au/documentation/adding-data-to-alveo/contributions/, page last accessed September 18, 2019.
As the orthographic transcriptions of the IRIAS corpus are underway, the amount of speech recorded for each speaker in the corpus was calculated via script by means of PRAAT’s To TextGrid (silences) function and by computing the amount of speech falling above a given silence threshold in dB. This computation was possible as the recordings have been collected by means of a head-mounted microphone capturing specifically the speaker’s voice (the interviewer’s voice can still be heard and transcribed, but being out of the direct reach of the microphone, it has a much lower intensity falling below the silence threshold set for the computation).
A further possible explanation might be either an effect of the specific research setting in which the participants feel that English is more appropriate for interacting with strangers. Alternatively, as suggested by one of the reviewers, it may even be an ability issue, e.g., they may only be used to discussing certain topics in certain languages, and lack the necessary vocabulary in another variety.
Medal of the Order of Australia.
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Acknowledgements
We are grateful for assistance from the following organisations and people, without whom the compilation of this corpus would not have been possible: Federation of Italian Migrant Workers and Families (Federazione Italiana Lavoratori e Famiglie, FILEF); Italian Association of Assistance (COASIT) Sydney; Italian Social Welfare Organisation of Wollongong (ITSOWEL); Italo-Australian Club Canberra; Sydney’s emigrants’ associations from Belluno, Rovigo and Treviso; “La Fiamma” bi-weekly newspaper; Nancy Romeo for her help in the recruitment of first and second-generation participants from Calabria; all the participants who took part and people who collaborated in the project. We thank the two anonymous reviewers for their careful reading and their many insightful comments, which helped us to improve our manuscript.
Funding
Preparation of this manuscript was made possible by an Endeavour Research Fellowship n. 6061/2017 awarded to V. Galatà by the Australian Department of Education and Training hosted by the third author at MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Australia. For the collection and the preparation of this corpus we acknowledge financial support: to V. Galatà in 2011 from the Italian National Research Council (Short-Term Mobility Grant n. 53653/2011) and in 2012 from Western Sydney University for a Visiting Fellowship with the MARCS Institute (HV 410/12); to C. Avesani (HV 1214/11) and M. Vayra (HV 256/12) from Western Sydney University (within the International Research Initiatives Scheme—IRIS—awarded to C. Best and B. Di Biase); to C. Best in 2013 from the Italian National Research Council (Short-Term Mobility Grant n. 39546/2013) and in 2015 from the Institute of Advanced Studies (ISA Senior Visiting Fellowship) from the University of Bologna, Italy; to the authors of this paper from Western Sydney University (Partnership Grant n. 20211/66165 with contributions from: Federazione Italiana Lavoratori e Famiglie, FILEF Sydney, Australia; MARCS Institute for Brain, Behaviour and Development, Western Sydney University - WSU, Australia; Department of Classic Philology and Italian Studies - FICLIT, University of Bologna, Italy; Institute of Cognitive Sciences and Technologies - ISTC, National Research Council - CNR, Italy).
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We note that this project was a fully integrated collaboration. Most responsibilities were shared, but the first author was solely responsible for several core aspects: VG was solely responsible for data curation, data visualisation and drafting of this report; VG and BDB shared responsibility for data collection; CA, CTB, and BDB shared responsibility for project administration. All authors shared the following tasks: project conceptualization, data validation, formal analysis, resources, funding acquisition, research assistant/student supervision, review & editing of this report.
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Appendices
Appendix 1
The list of target words (in Italian) presented to the participants by means of images. For each target word the expected outcomes in IPA transcription are also reported for both the dialect mode (respectively for participants from North Eastern Veneto and Central Veneto as documented in the AMDV by Tisato et al., 2013, and Southern Calabria) and the Italian mode (cf. Grosjean, 1998). Italian target words marked with an asterisk (*) have been presented to participants from Calabria only (see Sect. 4.2 for more details), while cells with a hyphen (-) indicate that the target word (e.g. image) was not presented to the participants for the given language mode.
# | Italian target word | Dialect mode | Italian mode | |||
---|---|---|---|---|---|---|
North Eastern Veneto | Central Veneto | Southern Calabriaa | Italian | English gloss | ||
1 | biscia | kaɾboˈnaθ | ˈbiːsa | ˈbiːso | ˈsɛrpi | skurˈzuni | /ˈbiʃːa/ | Snake |
2 | brace | ˈbɾoŋθe | ˈbɾoŋs̪e | ˈbːrasi | - /ˈbraʧe/ | Embers |
3 | burro | buˈtiːɾo | boˈtiːɾo | ˈburːu | - /ˈburːo/ | Butter |
4 | callo* | – | – | ˈkaLLu | /ˈkalːo/ | Callus |
5 | campanello* | – | – | kampaˈnɛLLu | /kampaˈnɛlːo/ | Doorbell |
6 | cancello* | – | – | kanˈʧeLLu | /kanˈʧelːo/ | Gate |
7 | capelli* | – | – | kaˈpiLLi | /kaˈpelːi/ | Hair |
8 | cassa | ˈkaːsa | ˈkaːsa | ˈkaʃːa | /ˈkasːa/ | Case |
9 | catena | kaˈðeːna | kaˈðeːna | kaˈtiːna | /kaˈteːna/ | Chain |
10 | cavallo* | – | – | kaˈvaLLu | /kaˈvalːo/ | Horse |
11 | cavezza | kaˈʋeːθa | kaˈʋeːs̪a | kaˈpitʦːa | /kaˈveʦːa/ | Halter |
12 | cazzuola | kaˈθɔːla | kaˈs̪ɔːʎa | kaʦˈʦɔla | /kaʦːuˈɔla/ | Trowel |
13 | cenere | ˈθeŋdɾo | ˈθeːneɾe | ˈs̪eːnəɾe | ˈʧinːari | /ˈʧenere/ | Ash |
14 | cento | ˈθeŋto | ˈs̪eŋto | ˈʧɛntu | /ˈʧɛnto/ | Hundred |
15 | centro | ˈθeŋtɾo | ˈs̪eŋtɾo | ˈʧɛnʈɽu | - /ˈʧɛntro/ | Center |
16 | ceppo | ˈθoːka | t̪al̝ˈpõŋ | ˈs̪ɔːka | ˈʦːukːu | - /ˈʧepːo/ | Stump |
17 | cervello* | – | – | ʧeraˈvɛLLu | /ʧerˈvɛlːo/ | Brain |
18 | cesta | ˈθesta | ˈs̪esta | ˈʧista | /ˈʧesta/ | Basket |
19 | chiave | ˈʧaːʋe | ˈʧaːʋe | ˈcaːvi | - /ˈkjave/ | Key |
20 | chiesa | ˈʧeːza | ˈʧeːza | ˈcɛːsa | /ˈkjɛza/ | Church |
21 | chiodo | ˈʧɔːð̞o | ˈʧɔːð̞o | ˈcɔːvu | /ˈkjɔdo/ | Nail |
22 | ciliegia | θaˈɾjeːza | saˈɾeːza | ʧeˈraːsa | /ʧiˈljɛʤa/ | Cherry |
23 | cimice | ˈθiːmes | ˈsiːmize | ˈʧimiʧa | /ˈʧimiʧe/ | Bug |
24 | cimitero | θimiˈtɛːɾo | s̪imiˈtɛːɾo | ʧimiˈtɛru | campuˈsantu | /ʧimiˈtɛro/ | Cemetery |
25 | cipolla | ˈθeola | s̪eːɣoʟ̞a | ʧiˈpuLLa | /ʧiˈpolːa/ | Onion |
26 | collo* | – | – | ˈkɔLLu | /ˈkɔlːo/ | Neck |
27 | coltello* | – | – | kurˈtɛLLu | /kolˈtɛlːo/ | Knife |
28 | cucchiaio | kuˈʧaːɾo | şkuˈljɛɾo | kuˈʧaːɾo | kucˈcara | /kukˈkjajo/ | Spoon |
29 | dado | ˈdað̞o | ˈdað̞o | ˈð̠að̠u | - /ˈdado/ | Dice |
30 | damigiana | d̪amiˈʥːana | d̪ʌmeˈaːna | ð̠amiʤˈʤana | /damiˈʤana/ | Jug |
31 | dente | ˈdeƞt | ˈdeƞt | ˈð̠ɛnti | /ˈdɛnte/ | Tooth |
32 | diga | ˈdiga | ˈdiga | ˈð̠iga | /ˈdiga/ | Dam |
33 | ditale | d̪iˈðjal | deˈaːe | d̪eˈale | d̪eˈaːe | jið̠iˈtala | /diˈtale/ | Thimble |
34 | doga | ˈð̞ɔːɣ̞a | ˈz̳oˑa | ˈðɔːga | /ˈdoga/ | Stave |
35 | fazzoletto | faθoˈl̞et | fas̪oˈeto | faʦːoˈletːu | /faʦːoˈletːo/ | Kerchief |
36 | folla* | – | – | ˈfuLLa | /ˈfolːa/ | crowd |
37 | fosso | ˈfɔsa | ˈfɔsa | ˈfɔsːa | /ˈfɔsːa/ | Trench |
38 | gallina* | – | – | gaLLina | /galˈlina/ | Hen |
39 | gallo* | – | – | ˈgaLLu | /ˈgalːo/ | Cock |
40 | giacca | jaˈket̪a | jaˈket̪a | ˈʤakːa | - /ˈʤakːa/ | Jacket |
41 | incudine | i͂ŋˈkuð̞e͂ƞ | iŋˈkuð̞ine | ˈŋkuðina | /inˈkudine/ | Anvil |
42 | laccio | ˈlaθː | ˈlas̪o | ˈlaʦːu | /ˈlaʧːo/ | Shoelace |
43 | martello* | – | – | marˈtɛLLu | /marˈtɛlːo/ | Hammer |
44 | mestolo | kaˈθɔːlo | kaˈθɔːt | kaˈs̪ɔːʟ̘o | kɔpˈpinu | /ˈmestolo/ | Ladle |
45 | molle* | – | – | ˈmɔLLu | /ˈmɔlːe/ | Soft |
46 | mollica* | – | – | muLLika | /molˈlika/ | Bread (soft part) |
47 | orecchie | ˈreːʧe | ˈreːʧe | ˈricːi | /oˈrekːje/ | Ears |
48 | osso | ˈɔːso | ˈɔːso | ˈɔːsu | /ˈɔsːo/ | Bone |
49 | palla* | – | – | ˈpaLLa | /ˈpalːa/ | Ball |
50 | patata | paˈtaːta | paˈtaːta | paˈtaːta | - /paˈtaːta/ | Potato |
51 | pennello* | – | – | pinˈneLLu | /penˈnɛlːo/ | Brush |
52 | pettine | ˈpɛːteŋ | ˈpɛt̪ənɛʎ̞a | ˈpetːinu | /ˈpɛtːine/ | Comb |
53 | pezza | ˈpeːθa | ˈpeːs̪a | ˈpeʦːa | /ˈpɛʦːa/ | Patch |
54 | pidocchio | peð̞ˈɔːʧo | ˈpjɔʧi | piˈð̠ocːu | /piˈdɔkːjo/ | Lice |
55 | pollo* | – | – | ˈpoLLu | /ˈpolːo/ | Chicken |
56 | presine | ʧaˈpin | ʧaˈpin | maˈpːini | - /preˈsine/ | Potholders |
57 | redini | ˈɾeːð̞ene | ˈɾeːð̞ene | ˈreːð̠ini | /ˈrɛdini/ | Reins |
58 | riccio | ˈɾiθː | poɹˈθɛls̻piˈnoːz̻o | ˈɾis̪o | ˈriʦːu | /ˈriʧːo/ | Hedgehog |
59 | rosso | ˈɾo:so | ˈɾo:so | ˈrusːu | /ˈrosːo/ | Red |
60 | ruota | ˈɾɔːð̞a | ˈɾɔːda | ˈɾɔːð̞a | ˈrɔːta | /ˈrwɔta/ | Wheel |
61 | salame | saˈlaːme | saˈʎ̞aːme | saˈlaːmi | - /saˈlaːme/ | Salami |
62 | salice | saˈleːθ | ˈsaleze | s̻t̪ɾoˈpaɾʊ | ˈsalaku | /ˈsaliʧe/ | Willow |
63 | scodella | skuˈð̞ɛːla | skuˈð̞ɛʎ̞a | skoˈð̠elːa | /skoˈdɛlːa/ | Bowl |
64 | secchio | ˈseːʧa | ˈs̳ɛːja | ˈseːʧa | ˈsecːu | /ˈsekːjo/ | Bucket |
65 | sega | ˈseːɣ̞a | ˈsjeːɣ̞a | ˈseːɣ̞a | ˈserːa | - /ˈsega/ | Saw |
66 | sella | ˈsɛːla | ˈsɛːʎ̞a | ˈselːa | - /ˈsɛlːa/ | Saddle |
67 | siepe | ˈθjeːza | ˈsjɛːve | siˈpaːla | /ˈsjɛpe/ | Hedge |
68 | sottana | ˈkɔːtola | ˈkɔːtoʎ̞a | suˈtːana | /sotˈtana/ | Soutane |
69 | spalle* | – | – | ˈspaLLi | /ˈspalːe/ | Shoulders |
70 | specchio | ˈspɛːʧo | ˈspɛːʧo | ˈspecːu | /ˈspɛkːjo/ | Mirror |
71 | stalla* | – | – | ˈstaLLa | /ˈstalːa/ | Shed |
72 | stella* | – | – | ˈstiLLa | /ˈstelːa/ | Star |
73 | tavolo | ˈtɔːla | ˈtɔːʟɜ | ˈtaːvulu | - /ˈtavolo/ | Table |
74 | teglia | ˈteːʧa | ˈteːʧa | ˈteʎːa | /ˈteʎːa/ | Baking |
75 | telaio | teˈlɛːɾ | teˈaːɾo | tiˈlaːru | /teˈlajo/ | Loom |
76 | tino | ˈtiːna | ˈtiːna | tiˈnaːs̪o | ˈtiːna | - /ˈtino/ | Vat |
77 | topo (sorcio) | ˈsoːrθ | ˈsoːɾde | ˈsoːɾðe | ˈsuːriʧi | /ˈtɔpo/ ~ /ˈsorʧo/ | Mouse |
78 | torchio | ˈtɔɾʧo | ˈtɔɾʧo | ˈtorcu | /ˈtɔrkjo/ | Press |
79 | toro | ˈtɔːɾo | ˈtɔːɾo | ˈtoːru | – | Bull |
80 | treccia | ˈdɾeːθa | ˈdɾeːs̪a | ˈʈɽiʦːa | ʈɽiʦːu | /ˈtreʧːa/ | Braid |
81 | uccello* | – | – | aˈʧːeLLu | /utˈʧɛlːo/ | Bird |
82 | vallone* | – | – | vaLLuni | /valˈlone/ | Deep valley |
83 | zappa | ˈθaːpa | ˈsaːpa | ˈs̪aːpa | ˈʦːapːa | ʦːaˈpːuni | /ˈʦapːa/ | Hoe |
84 | zoccoli | ˈθɔːkoi | s̪oˈpɛi | ˈs̪ɔːkoi | ˈʦːokːula | /ˈʦɔkːoli/ | Clogs |
85 | zoppo | ˈθɔːt | ˈs̪ɔːto | ˈʦːopːu | /ˈʣɔpːo/ | Lame |
86 | zucchero | ˈθuːkero | ˈs̪uːkaro | ˈʦːukːaru | - /ˈʣukːero/ | Sugar |
Appendix 2
Transcription guidelines used in the IRIAS corpus. Unless otherwise stated, all words are transcribed using lower case letters (exception is made for the English first person pronoun “I”).
Category | Condition | Markup | Example | Explanation |
---|---|---|---|---|
Orthography and spelling | Spelled words | Capitalise and space separate letters | I said you Y O U | Individual letters spelled out, with spaces in-between |
Sensitive information | Capitalise 1st letter and connect compound words for names, places, streets, professions, etc. with - [dash] | James, Bologna New-South-Wales Via-Garibaldi, Piazza-Verdi | This will facilitate the anonymization of sensitive information if needed (the dash keeps words together) | |
Acronyms | Capitalise letters | COASIT | All letters in caps, no space in-between | |
Contractions | Transcribe as spoken | can’t, I’m gonna g’ha, l’albero | If you hear a contraction, write it as a contracted form | |
Stressed words | Use accented characters, no other diacritics | perchè, però | Check an Italian dictionary if in doubt | |
Numbers | Spell out | twenty-five, one oh nine, one hundred, thirteen | Write out English numbers in full (with dashes where required; e.g. from 21 to 99). No dashes for Italian numbers | |
Punctuation | ? [question mark] / short pause // pause > 0.5 s | what ? he was / happy he was // happy | Do not use commas. Precede ? by space Short and long pauses are marked in a separate interval (not within the text interval). Limited to these symbols only: if you hear a pause, use either / or // | |
Disfluent speech | Filled pauses, interjections | No special markup: transcribe literally | ehm, ahm, uhm, uh, huh, yeah, mh | Use standardised spelling (keep track of actual spelling used in order to implement a detailed list) |
Partial words | - [dash] | absolu- | Speaker-produced partial words are indicated with a dash attached to the word (e.g. no spaces). Transcribe as much of the word as you hear | |
Speaker restarts | -- [double dash] | I was -- I had to go | Used when the speaker stops short and then repeats himself, or abandons the utterance completely, restarting with a new sentence | |
Mispronounced or non-standard words | * [asterisk] | *knowledgement | Transcribe mispronounced words, speech errors, lapsus or idiosyncratic vocabulary using standard orthography: attach asterisk at the beginning of the targeted part of the word (e.g. no spaces) | |
Additional markup | Unintelligible speech, human noise | (speech) <usb> | they lived (close to) <usb> | Text in parentheses indicates the transcriber’s best decoding attempt, while <usb> marks an entirely unintelligible segment, passage, word or other human noise (laughter, chuckle etc.) |
Non speech events | <nib> | this one <nib> | <nib> indicates noise (e.g. bangs s fist on table) | |
Code-switching | @ to English § to Italian & to dialect &* to Italianized dialect @* to Italianized English | dice @you know@ wait §mi disse§ è un &bizat& le &*bronze&* una @*cappa@* di latte | Put the character before and after one word or sentence or part of speech |
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Galatà, V., Avesani, C., Best, C.T. et al. The Italian Roots in Australian Soil (IRIAS) multilingual speech corpus. Speech variation in two generations of Italo-Australians. Lang Resources & Evaluation 56, 37–78 (2022). https://doi.org/10.1007/s10579-021-09539-3
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DOI: https://doi.org/10.1007/s10579-021-09539-3