Detecting Quotations in Spoken...
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Aim of the research ARs in Spoken Dialogues VS Written Text The importance of prosody for detecting quotations Attribution Relations in Written Texts Annotation scheme for ARs customized for dialogues ARs in Spoken Dialogues Attribution Relations (ARs) connect quotations, opinions and other third party information to their rightful source. The work done so far for automatic detection of ARs has dealt only with written text. Detecting Attributions in speech is important for: ● speaker identification ● dialogue structure ● extraction of references to named entities ● dialogue parsing The crucial role played by punctuation in written texts is replaced in speech by prosody. To detect ARs in speech we should consider both the linguistic and the acoustic levels. Knowing the source of a given piece of information changes the way we intepret and rely on it. Current approaches to automatic ARs extraction rely on lexical cues and punctuation, which can be crucial to detect the extent of the attributed span (Content). PARC (Pareti 2012) is a corpus of news articles. The Speech Attribution Relations Corpus (SARC) is a corpus of informal telephone conversations. Differences ● punctuation absent and replaced by prosody ● different cue verbs (he's like, he goes) ● syntax less reliable since it's all fragmented I'd like to thank Bonnie Webber for her suggestions and comments. Couper-Kuhlen, E. (1993). English speech rhythm: Form and function in everyday verbal interaction (Vol. 25). John Benjamins. Bolden, G. (2004). The quote and beyond: defining boundaries of reported speech in conversational Russian. Journal of pragmatics, 36(6), 1071-1118. References In spoken language, prosody replaces the role of punctuation. Klewitz & Couper-Kuhlen (1999) found prosodic features which are “flags” of reported speech: 2. Quotations without Cue. Which is the Content of the quotation and who is the author? Detecting Quotations in Spoken Dialogues Building the Corpus Alessandra Cervone [email protected] Acknowledgements Speaker 2: outLine Speaker 1: inLine DATA: Telephone conversations with each speaker recorded on a different track ACOUSTIC ANNOTATION: ● Transcription ● Annotation of the Content of the quotations TOKENIZATION LINGUISTIC ANNOTATION: Annotation of the remaining ARs: Sources, Cues and Supplements SARC PARC REGISTER Informal Formal MEAN Oral Written GENRE Dialogue News(WSJ) TOKENS 12k, 1h30 1.139k AR/1k TOKENS 12,4 9,2 The authors have not supported their claims with any statistics. Can these “flags” be identified and what is their role in marking the presence of reported speech? Klewitz, G., & Couper-Kuhlen, E. (1999). Quote-unquote? The role of prosody in the contextualization of reported speech sequences. Universität Konstanz, Philosophische Fakultät, Fachgruppe Sprachwissenschaft. Pareti, S., & Prodanof, I. (2010). Annotating Attribution Relations: Towards an Italian Discourse Treebank. In LREC. Pareti, S., (2012). A Database of Attribution Relations. In Proceedings of the Eighth conference on International Language Resources and Evaluation LREC12, Istanbul, 23-25 May 2012. Conclusions and Future Work The examples presented shows that prosody plays a crucial role in determining presence and extent of ARs in speech. Future work: ● Annotate other 3 hours of dialogues ● Acoustic Analysis: Test the claims made by Klewitz & Couper-Kuhlen (1999) ● Linguistic Analysis: Contrastively evaluate the lexical realisation of ARs in speech (SARC) and written texts (SARC) ● Shifts in pitch register ● Shifts in intensity ● Shifts in the rhythm Peter Bell [email protected] Silvia Pareti [email protected] *“Fading out” (Bolden 2004) are cases where the ending boundary of a quotation is not clear. . Università degli Studi di Pavia 1. It seems a quotation but it is not: so I said to him when you left do you remember I told you I said to him don't forget Dave if you ever get in trouble give us a call you never know your luck outLine: so I said to him when you left do you remember I told you I said to him don't forget Dave if you ever get in trouble give us a call you never know your luck No No No No S1 S1 60 65 70 75 80 85 she wouldn't I said well but I said at the end of the day I said you could sell your house what for a loft and I said well yes if you really didn't have any money you'd have to sell it for a loft buy something smaller well I'm not going to do that and I thought well then you haven't not got any money then have you it's not really the same thing inLine: By only considering linguistic cues we would miss reported Speaker2 quotations. Prosody gives us the key to the correct interpretation. LEGENDA: Quotes reported Speaker 1 AR set Quotes reported Speaker 2 AR alone in its set Prasad, R., Dinesh, N., Lee, A., Joshi, A., & Webber, B. (2006, July). Annotating attribution in the penn discourse treebank. In Proceedings of the Workshop on Sentiment and Subjectivity in Text (pp. 31-38). Association for Computational Linguistics. 400 Hz 50 dB 100 dB 75 Hz PULSES INTENSITY PITCH TEXT No No No No S1 S1 125,0 145,0 165,0 185,0 dB Hz PAUSES ● Long pause just before the beginning of the Content PITCH ● Decrease of the pitch register with a stabilisation when the Content begins INTENSITY ● Decrease in the intensity with a stabilisation when the Content begins Data suggest a difference in the prosodic marking between the Content of the AR and the rest of the text. Preliminary Acoustic Analysis Mean PITCH Mean INTENSITY No No S1 No S1 No S1 S2 No S1 S1 S1 S2 No S1 S1(F) 60 65 70 75 80 PULSES PITCH INTENSITY TEXT 50 dB 100 dB 75 Hz 400 Hz Preliminary Acoustic Analysis PAUSES ● Long pause before both switches between the two reported speakers ● Long pause before the Fading out INTENSITY ● Shift to a higher Intensity before switches between normal text and Contents. ● The intensity gets particularly high in the two cases in which two different speakers are reported. Mean INTENSITY Annotation scheme for ARs (Pareti, 2010) * ] [ [ [ ] ]
Transcript of Detecting Quotations in Spoken...
Aim of the research
ARs in Spoken Dialogues VS Written Text
The importance of prosody for detecting quotations
Attribution Relations in Written Texts
Annotation scheme for ARs customized for dialogues
ARs in Spoken Dialogues
Attribution Relations (ARs) connect quotations, opinions and other third party information to their rightful source. The work done so far for automatic detection of ARs has dealt only with written text.
Detecting Attributions in speech is important for:● speaker identification● dialogue structure● extraction of references to named entities● dialogue parsing
The crucial role played by punctuation in written texts is replaced in speech by prosody. To detect ARs in speech we should consider both the linguistic and the acoustic levels.
Knowing the source of a given piece of information changes the way we intepret and rely on it. Current approaches to automatic ARs extraction rely on lexical cues and punctuation, which can be crucial to detect the extent of the attributed span (Content).
PARC (Pareti 2012) is a corpus of news articles.The Speech Attribution Relations Corpus (SARC) is a corpus of informal telephone conversations.
Differences ● punctuation absent and replaced by prosody● different cue verbs (he's like, he goes)● syntax less reliable since it's all fragmented
I'd like to thank Bonnie Webber for her suggestions and comments.
Couper-Kuhlen, E. (1993). English speech rhythm: Form and function in everyday verbal interaction (Vol. 25). John Benjamins.
Bolden, G. (2004). The quote and beyond: defining boundaries of reported speech in conversational Russian. Journal of pragmatics, 36(6), 1071-1118.
References
In spoken language, prosody replaces the role of punctuation.
Klewitz & Couper-Kuhlen (1999) found prosodic features which are “flags” of reported speech:
2. Quotations without Cue. Which is the Content of the quotation and who is the author?
Detecting Quotations in Spoken Dialogues
Building the Corpus
Alessandra Cervone [email protected]
Acknowledgements
Speaker 2: outLineSpeaker 1: inLine
DATA: Telephone conversations with each
speaker recorded on a different track
ACOUSTIC ANNOTATION:● Transcription
● Annotation of the Content of the quotations
TOKENIZATION
LINGUISTIC ANNOTATION: Annotation of the remaining ARs: Sources, Cues and Supplements
SARC PARC
REGISTER Informal Formal
MEAN Oral WrittenGENRE Dialogue News(WSJ)
TOKENS 12k, 1h30 1.139kAR/1k TOKENS 12,4 9,2
The authors have not supported their claims with any statistics. Can these “flags” be identified and what is their role in marking the presence of reported speech?
Klewitz, G., & Couper-Kuhlen, E. (1999). Quote-unquote? The role of prosody in the contextualization of reported speech sequences. Universität Konstanz, Philosophische Fakultät, Fachgruppe Sprachwissenschaft.
Pareti, S., & Prodanof, I. (2010). Annotating Attribution Relations: Towards an Italian Discourse Treebank. In LREC.
Pareti, S., (2012). A Database of Attribution Relations. In Proceedings of the Eighth conference on International Language Resources and Evaluation LREC12, Istanbul, 23-25 May 2012.
Conclusions and Future WorkThe examples presented shows that prosody plays a crucial role in determining presence and extent of ARs in speech.
Future work: ● Annotate other 3 hours of dialogues● Acoustic Analysis: Test the claims made by Klewitz & Couper-Kuhlen (1999) ● Linguistic Analysis: Contrastively evaluate the lexical realisation of ARs in speech (SARC) and written
texts (SARC)
● Shifts in pitch register● Shifts in intensity● Shifts in the rhythm
Peter Bell [email protected]
Silvia Pareti [email protected]
*“Fading out” (Bolden 2004) are cases where the ending boundary of a quotation is not clear..
Università degli Studi di Pavia
1. It seems a quotation but it is not:
so I said to him when you left do you remember I told you I said to him don't forget Dave if you ever get in trouble give us a call you never know your luck
outLine: so I said to him when you left do you remember I told you I said to him don't forget Dave if you ever get in trouble give us a call you never know your luck
No No No No S1 S1606570758085
she wouldn't I said well but I said at the end of the day I said you could sell your house what for a loft and I said well yes if you really didn't have any money you'd have to sell it for a loft buy something smaller well I'm not going to do that and I thought well then you haven't not got any money then have you it's not really the same thing
inLine:
By only considering linguistic cues we would miss reported Speaker2 quotations. Prosody gives us the key to the correct interpretation.
LEGENDA: Quotes reported Speaker 1 AR set Quotes reported Speaker 2 AR alone in its set
Prasad, R., Dinesh, N., Lee, A., Joshi, A., & Webber, B. (2006, July). Annotating attribution in the penn discourse treebank. In Proceedings of the Workshop on Sentiment and Subjectivity in Text (pp. 31-38). Association for Computational Linguistics.
400 Hz
50 dB
100 dB
75 Hz
PULS
ESIN
TEN
SITY
PITC
HTE
XT
No No No No S1 S1125,0
145,0
165,0
185,0
dB
Hz
PAUSES ● Long pause just before the
beginning of the Content
PITCH● Decrease of the pitch
register with a stabilisation when the Content begins
INTENSITY● Decrease in the intensity
with a stabilisation when the Content begins
Data suggest a difference in the prosodic marking between the Content of the AR and the rest of the text.
Preliminary Acoustic Analysis
Mea
n PI
TCH
Mea
n IN
TEN
SITY
No No S1 No S1 No S1 S2 No S1 S1 S1 S2 No S1 S1(F)60
65
70
75
80
PULS
ESPI
TCH
INTE
NSI
TYTE
XT
50 dB
100 dB
75 Hz
400 Hz
Preliminary Acoustic Analysis
PAUSES● Long pause before both switches between the two reported speakers● Long pause before the Fading out
INTENSITY● Shift to a higher Intensity before switches between normal text and Contents. ● The intensity gets particularly high in the two cases in which two different speakers are reported.
Mea
n IN
TEN
SITY
Annotation scheme for ARs (Pareti, 2010)
*
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[
[
]
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