Abstract
A suite of related online and offline analysis and visualisation tools for training students of phonetics in the acoustics of prosody is described in detail. Prosody is informally understood as the rhythms and melodies of speech, whether relating to words, sentences, or longer stretches of discourse, including dialogue. The aim is to contribute towards bridging the epistemological gap between phonological analysis, based on the linguist’s intuition together with structural models, on the one hand, and, on the other hand, phonetic analysis based on measurements and physical models of the production, transmission (acoustic) and perception phases of the speech chain. The toolkit described in the present contribution applies to the acoustic domain, with analysis of the low frequency (LF) amplitude modulation (AM) and frequency modulation (FM) of speech, with spectral analyses of the demodulated amplitude and frequency envelopes, in each case as LF spectrum and LF spectrogram. Clustering functions permit comparison of utterances.
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- 1.
http://wwwhomes.uni-bielefeld.de/gibbon/CRAFT/; code accessible on GitHub.
References
Arjmandi, M.K., Dilley, L.C., Lehet, M.: A comprehensive framework for F0 estimation and sampling in modeling prosodic variation in infant-directed speech. In: Proceedings of the 6th International Symposium on Tonal Aspects of Language, Berlin, Germany (2018)
Barbosa, P.A.: Explaining cross-linguistic rhythmic variability via a coupled-oscillator model of rhythm production. Speech Prosody 2002, 163–166 (2002)
Boersma, P.: Praat, a system for doing phonetics by computer. Glot Int. 5(9/10), 341–345 (2001)
Camacho, A.: SWIPE: A Sawtooth Waveform Inspired Pitch Estimator for Speech and Music. Ph.D. thesis, University of Florida (2007)
Cummins, F., Port, R.: Rhythmic constraints on stress timing in English. J. Phon. 1998(26), 145–171 (1998)
De Cheveigné, A., Kawahara, H.: YIN, a fundamental frequency estimator for speech and music. J. Acoust. Soc. Am. 111(4), 1917–1930 (2002)
Garg, D.: SWIPE pitch estimator (2018). https://github.com/dishagarg/SWIPE. [PySWIPE]
Gaspari, D.: Mandarin Tone Trainer. Master’s thesis, Harvard Extension School (2016). https://github.com/dgaspari/pyrapt
Gibbon, D.: The future of prosody: It’s about time. Proc. Speech Prosody 9 (2018). https://www.isca-speech.org/archive/SpeechProsody_2018/pdfs/_Inv-1.pdf
Gibbon, D.: Rhythm zone theory: speech rhythms are physical after all. In: Wrembel, M., Kiełkiewicz-Janowiak, A., Gąsiorowski, P. (eds.) Approaches to the Study of Sound Structure and Speech. Interdisciplinary Work in Honour of Katarzyna Dziubalska-Kołaczyk. Routledge, London (2019). https://arxiv.org/abs/1902.01267
Gibbon, D.: CRAFT: A Multifunction Online Platform for Speech Prosody Visualisation (2019). https://arxiv.org/pdf/1903.08718.pdf
Gibbon, D.: The rhythms of rhythm. J. Int. Phonetic Assoc. First View 1–33 (2021). https://doi.org/10.1017/S0025100321000086
Guyot, P.: Fast Python implementation of the Yin algorithm (2018). https://github.com/patriceguyot/Yin/
Hermansky, H.: History of modulation spectrum in ASR. In: Proceedings of the ICASSP 2010 (2010)
Hess, W.: Pitch Determination of Speech Signals: Algorithms and Devices. Springer, Berlin (1983). https://doi.org/10.1007/978-3-642-81926-1
Inden, B., Malisz, Z., Wagner, P., Wachsmuth, I.: Rapid entrainment to spontaneous speech: a comparison of oscillator models. In: Miyake, N., Peebles, D., Cooper, R.P. (eds.) Proceedings of the 34th Annual Conference of the Cognitive Science Society. Cognitive Science Society, Austin (2012)
Jouvet, D., Laprie, Y.: Performance analysis of several pitch detection algorithms on simulated and real noisy speech data. In: 25th European Signal Processing Conference (2017)
Klessa, K.: Annotation Pro. Enhancing Analyses of Linguistic and Paralinguistic Features in Speech. Wydział Neofilologii UAM, Poznań (2016)
Martin, P.: WinPitch: un logiciel d’analyse temps réel de la fréquence fondamentale fonctionnant sous Windows. Actes des XXIV Journées d’Étude sur la Parole, Avignon 224–227 (1996)
Rabiner, L.R., Cheng, M.J., Rosenberg, A.E., McGonegal, C.A.: A comparative performance study of several pitch detection algorithms. IEEE Trans. Acoust. Speech Sig. Process. ASSP-24(5), 399–418 (1976)
Schmitt, B.J.B.: AMFM_decompy (2014). [PyYAAPT]. https://github.com/bjbschmitt/AMFM_decompy
Sjölander, K., Beskow, J.: Wavesurfer – an open source speech tool. Proc. Interspeech 464–467 (2000). http://www.speech.kth.se/wavesurfer/
Talkin, D.: A robust algorithm for pitch tracking (RAPT). In: Kleijn, W.B., Palatal, K.K. (eds.) Speech Coding and Synthesis, pp. 497–518. Elsevier Science B.V. (1995)
Talkin, D.: Reaper: Robust Epoch And Pitch EstimatoR (2014). https://github.com/google/REAPER
Tilsen, S., Johnson, K.: Low-frequency Fourier analysis of speech rhythm. J. Acoust. Soc. Am. 124(2), EL34–EL39 (2008). [PubMed: 18681499]
Tilsen, S., Arvaniti, A.: Speech rhythm analysis with decomposition of the amplitude envelope: characterizing rhythmic patterns within and across languages. J. Acoust. Soc. Am. 134, 628 (2013)
Todd, N.P.M., Brown, G.J.: A computational model of prosody perception. ICSLP 94, 127–130 (1994)
TraunmĂ¼ller, H.: Conventional, biological, and environmental factors in speech communication: a modulation theory. In Dufberg, M., Engstrand, O. (eds.) PERILUS XVIII: Experiments in Speech Process, pp. 1–19. Department of Linguistics, Stockholm University, Stockholm (1994). [Also in Phonetica 51, 170–183 (1994)]
Xu, Y.: ProsodyPro – a tool for large-scale systematic prosody analysis. In: Tools and Resources for the Analysis of Speech Prosody (TRASP 2013), Aix-en-Provence, France, pp. 7–10 (2013)
Zahorian, S.A., Hu, H.: A spectral/temporal method for robust fundamental frequency tracking. J. Acoust. Soc. Am. 123(6), 4559–4571 (2008). [YAAPT]
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Gibbon, D. (2022). The Phonetic Grounding of Prosody: Analysis and Visualisation Tools. In: Vetulani, Z., Paroubek, P., Kubis, M. (eds) Human Language Technology. Challenges for Computer Science and Linguistics. LTC 2019. Lecture Notes in Computer Science(), vol 13212. Springer, Cham. https://doi.org/10.1007/978-3-031-05328-3_3
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