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SRI Speech-Based Collaborative Learning Corpus
Richey, Colleen; D'Angelo, Cynthia; Alozie, Nonye. - : Linguistic Data Consortium, 2019. : https://www.ldc.upenn.edu, 2019
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SRI Speech-Based Collaborative Learning Corpus ...
Richey, Colleen; D'Angelo, Cynthia; Alozie, Nonye. - : Linguistic Data Consortium, 2019
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3
SRI-FRTIV
Shriberg, Elizabeth; Kathol, Andreas; Graciarena, Martin. - : Linguistic Data Consortium, 2017. : https://www.ldc.upenn.edu, 2017
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SRI-FRTIV ...
Kathol, Andreas; Shriberg, Elizabeth; Graciarena, Martin. - : Linguistic Data Consortium, 2017
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5
Finding the Structure of Documents
In: Multilingual natural language processing applications ; https://hal-amu.archives-ouvertes.fr/hal-01194260 ; Zitouni, I. and Bickel, D.M. Multilingual natural language processing applications, IBM Press, pp.21--48, 2011, 978-0137151448 (2011)
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6
The SRI NIST 2010 Speaker Recognition Evaluation System (PREPRINT)
In: DTIC (2011)
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7
The CALO meeting assistant system
In: Institute of Electrical and Electronics Engineers. IEEE transactions on audio, speech and language processing. - New York, NY : Inst. 18 (2010) 6, 1601-1611
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8
EduSpeak: a speech recognition and pronunciation scoring toolkit for computer-aided language learning applications
In: Language testing. - London : Sage 27 (2010) 3, 401-418
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OLC Linguistik
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9
Speaker adaptation of language and prosodic models for automatic dialog act segmentation of speech
In: Speech communication. - Amsterdam [u.a.] : Elsevier 52 (2010) 3, 236-245
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10
A Corpus Analysis of Patterns of Age-Related Change in Conversational Speech
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11
Prosodic Similarities of Dialog Act Boundaries Across Speaking Styles
In: Language and Lingusitics Monograph Series: Linguistic Patterns in Spontaneous Speech ; https://hal-amu.archives-ouvertes.fr/hal-01194276 ; Language and Lingusitics Monograph Series: Linguistic Patterns in Spontaneous Speech, 2009, pp.213-239 (2009)
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12
Comparing Evaluation Metrics for Sentence Boundary Detection
In: DTIC (2007)
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13
Comparison of Evaluation Metrics for Sentence Boundary Detection
In: DTIC (2007)
Abstract: Automatic detection of sentences in speech is useful to enrich speech recognition output and ease subsequent language processing modules. In the recent NIST evaluations for this task, an error rate was used to evaluate system performance. A variety of metrics such as F-measure, ROC or DET curves have also been explored in other studies. This paper aims to take a closer look at the evaluation issue for sentence boundary detection. We employ different metrics NIST error rate, classification error rate per word boundary, precision and recall, ROC curve, DET curve, precision-recall curve, and the area under the curves, to compare different system output. In addition we use two different corpora in order to evaluate the impact of different imbalance in the data set. We show that it is helpful to use curves as well as a single performance metric, and that different curves show different advantages in visualization. Furthermore, the data skewness also has an impact on the metrics. ; Prepared in cooperation with University of Texas, Austin, TX; and International Computer Science Institute, Berkeley, CA.
Keyword: *MEASURES OF EFFECTIVENESS; *PARSERS; AUC(AREA UNDER RECEIVER OPERATING CHARACTERISTIC CURVE); Computer Programming and Software; CTS(CONVERSATIONAL TELEPHONE SPEECH); DET CURVES; GRAMMARS; Information Science; LANGUAGE; Linguistics; LM(LANGUAGE MODELS); METRICS; NATURAL LANGUAGE; NIST(NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY); ROC CURVES; ROC(RECEIVER OPERATING CHARACTERISTIC); SENTENCE BOUNDARIES; SOCIAL COMMUNICATION; SPEECH PROCESSING; SPEECH RECOGNITION; Voice Communications; WORDS(LANGUAGE)
URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA534445
http://www.dtic.mil/docs/citations/ADA534445
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14
Speaker Adaptation of Language Models for Automatic Dialog Act Segmentation of Meetings
In: DTIC (2007)
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15
A study in machine learning from imbalanced data for sentence boundary detection in speech
In: Computer speech and language. - Amsterdam [u.a.] : Elsevier 20 (2006) 4, 468-494
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OLC Linguistik
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16
Enriching speech recognition with automatic detection of sentence boundaries and disfluencies
In: Institute of Electrical and Electronics Engineers. IEEE transactions on audio, speech and language processing. - New York, NY : Inst. 14 (2006) 5, 1526-1540
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OLC Linguistik
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17
Combining Prosodic, Lexical and Cepstral Systems for Deceptive Speech Detection
Hirschberg, Julia Bell; Enos, Frank; Graciarena, Martin. - : Proceedings IEEE ICASSP 2006, 2006
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18
Combining Prosodic, Lexical and Cepstral Systems for Deceptive Speech Detection ...
Hirschberg, Julia Bell; Enos, Frank; Graciarena, Martin. - : Columbia University, 2006
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19
On Speaker-Specific Prosodic Models for Automatic Dialog Act Segmentation of Multi-Party Meetings
In: DTIC (2006)
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20
Modeling prosodic feature sequences for speaker recognition
In: Speech communication. - Amsterdam [u.a.] : Elsevier 46 (2005) 3-4, 455-472
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