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Erschienen in:
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2015 | OriginalPaper | Buchkapitel

4. Non-linguistic Speech Processing

verfasst von : Sunil Kumar Kopparapu

Erschienen in: Non-Linguistic Analysis of Call Center Conversations

Verlag: Springer International Publishing

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Abstract

There has been an increase in spoken interaction between people from different geographies or different cultural backgrounds prominently in the call center scenario.

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Vorheriges Kapitel Call Center Linguistic Analytics
Nächstes Kapitel Case Study
Literatur
1.
M.A. Pandharipande, S.K. Kopparapu, Real time speaking rate monitoring system. in International Conference on Signal Processing, Communications and Computing (ICSPCC), Sept. 2011, pp. 1–4
2.
A. Janet, K. Kenneth, The effect of foreign accent and speaking rate on native speaker comprehension. Lang. Learn. 38, 561–613 (1988)CrossRef
3.
J. Murray, M. Tracey, The effects of speaking rate on listener evaluations of native and foreign-accented speech. Lang. Learn. 48, 159–182 (1998)CrossRef
4.
J. Yuan, M. Liberman, C. Cieri, Towards an integrated understanding of speaking rate in conversation. Proc. Interspeech 2006, 541–544 (2006)
5.
A. Bradlow, D. Pisoni, Recognition of spoken words by native and non-native listeners: talker-, listener-, and item-related factors. J. Acoust. Soc. Am. 106(4), 2074–2085 (1999)CrossRef
6.
D. O’ Sullivan, Caller adaptive voice response system. US Patent 5,493,608, 20 February 1996
7.
M.J. Munro, T.M. Derwing, The effects of speaking rate on listener evaluations of native and foreign-accented speech. Lang. Learn. 48(2), 159–182 (1998)CrossRef
8.
M.J. Munro, T.M. Derwing, Modeling perceptions of the accentedness and comprehensibility of l2 speech the role of speaking rate. Stud. Second Lang. Acquis. 23, 451–468 (2001)
9.
D O’ Sullivan, Using an adaptive voice user interface to gain efficiencies in automated calls. Whitepaper, Interactive Digital, (2009)
10.
I. Ahmed, M. Pandharipande, S.K. Kopparapu, Speakrite: A Real Time Tool for Speaking Rate Monitoring. in SiMPE, (2012)
11.
N.H. De Jong, T. Wempe, Praat script to detect syllable nuclei and measure speech rate automatically. Behav. Res. Methods 41, 385–390 (2009)CrossRef
12.
P. Boersma, Accurate Short-term Analysis of the Fundamental Frequency and the Harmonics-to-Noise Ratio of a Sampled Sound. in institute of phonetic sciences, University of Amsterdam, Proceedings 17, (1993)
13.
P. Francois, C. Christophe, M. Egidio, Across-language perspective on speech information rate. Language, Sept. 2011, pp. 539–558
14.
J. Scott, Yaruss. Converting between word and syllable counts in children’s conversational speech samples. J. Fluency Disord. 25(4), 305–316 (2000)CrossRef
15.
P. Vepreka, M. Scordilis, Analysis, enhancement and evaluation of five pitch determination techniques. Speech Commun. 37, 249–270 (2002)CrossRef
16.
A. Camacho, Swipe: a sawtooth waveform inspired pitch estimator for speech and music. PhD thesis, University of Florida, Gainesville, FL, USA, 2007, AAI3300722
17.
M.G. Christensen, A. Jakobsson, Multi-pitch Estimation. Synthesis Lectures on Speech and Audio Processing. Morganand Claypool Publishers, (2009)
18.
P.N. Garner, M. Cernak, P. Motlicek, A simple continuous pitch estimation algorithm. IEEE Signal Process. Lett. 20(1), 102–105 (2013)CrossRef
19.
M. Radmard, M. Hadavi, M. Nayebi, A new method of voiced unvoiced classification based on clustering. J. Signal Inform. Process. 2, 336–347 (2011)CrossRef
20.
K.I. Molla, K. Hirose, N. Minematsu, and K. Hasan. Voiced/unvoiced detection of speech signals using empirical mode decomposition model. in International Conference on Information and Communication Technology, ICICT ’07, March 2007, pp. 311–314
21.
R.G. Bachu, S. Kopparthi, B. Adapa, B.D. Barkana. Voiced/Unvoiced Decision for Speech Signals Based on Zero-Crossing Rate and Energy. in Khaled Elleithy, editor, Advanced Techniques in Computing Sciences and Software Engineering, Springer, Netherlands, 2010, pp. 279–282
22.
I. Ahmed, M. Pandharipande, S.K. Kopparapu, Speakrite: monitoring speaking rate on mobile phone in real time. Int. J. Mobile Human Comput. Interac. 5(1), 62–69 (2013)CrossRef
23.
24.
I. Luengo, E. Navas, I. Hernáez, Feature analysis and evaluation for automatic emotion identification in speech. IEEE Trans. Multimedia 12(6), 490–501 (2010)CrossRef
25.
M. Shah, L. Miao, C. Chakrabarti, A. Spanias, A speech emotion recognition framework based on latent dirichlet allocation: algorithm and fpga implementation. in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2013, pp. 2553–2557
26.
B. Schuller, A. Batliner, S. Steidl, D. Seppi, ecognising realistic emotions and affect in speech: state of the art and lessons learnt from the first challenge. Speech Commun. Sens. Emot. Affect - Facing Realism Speech Process. 53(910), 1062–1087 (2011)
27.
I. Lefter, Automatic emotion enalysis based on speech, (2009)
28.
C. Busso, Z. Deng, S. Yildirim, M. Bulut, C.M. Lee, A. Kazemzadeh, S.Lee, U. Neumann, S. Narayanan, Analysis of emotion recognition using facial expressions, speech and multimodal information. in Proceedings of the 6th International Conference on Multimodal Interfaces, ICMI ’04, New York, NY, USA, 2004, pp. 205–211
29.
R. Lpez-Czar, J. Silovsky, M. Kroul, Enhancement of emotion detection in spoken dialogue systems by combining several information sources. Speech Commun. Sens. Emot. Affect - Facing Realism Speech Process. 53(910), 1210—1228 (2011)
30.
I. Stankovic, M. Karnjanadecha, V. Delic, Improvement of thai speech emotion recognition by using face feature analysis. in International Symposium on Intelligent Signal Processing and Communications Systems (ISPACS), Dec 2011, pp. 1–5
31.
T.-L. Pao, C.-H. Wang, and Y.-J. Li, A study on the search of the most discriminative speech features in the speaker dependent speech emotion recognition. in Fifth International Symposium on Parallel Architectures, Algorithms and Programming (PAAP), Dec 2012, pp. 157–162
32.
Metadaten
Titel
Non-linguistic Speech Processing
verfasst von
Sunil Kumar Kopparapu
Copyright-Jahr
2015
Buch
Non-Linguistic Analysis of Call Center Conversations

Print ISBN: 978-3-319-00896-7

Electronic ISBN: 978-3-319-00897-4

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-3-319-00897-4_4

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