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How Many Ways Can You Vocalize Emotion? Introducing an Audio Corpus of Acted EmotionKowallis, Logan Ricks 01 April 2021 (has links)
Emotion recognition from facial expressions has been thoroughly explored and explained through decades of research, but emotion recognition from vocal expressions has yet to be fully explained. This project builds on previous experimental approaches to create a large audio corpus of acted vocal emotion. With a large enough sample size, both in number of speakers and number of recordings per speaker, new hypotheses can be explored for differentiating emotions. Recordings from 131 subjects were collected and made available in an online corpus under a Creative Commons license. Thirteen acoustic features from 120 subjects were used as dependent variables in a MANOVA model to differentiate emotions. As a comparison, a simple neural network model was evaluated for its predictive power. Additional recordings intended to exhaust possible ways to express emotion are also explored. This new corpus matches some features found in previous studies for each of the four emotions included (anger, fear, happiness, and sadness).
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Perception of prosody by cochlear implant recipientsVan Zyl, Marianne January 2014 (has links)
Recipients of present-day cochlear implants (CIs) display remarkable success with speech recognition in quiet, but not with speech recognition in noise. Normal-hearing (NH) listeners, in contrast, perform relatively well with speech recognition in noise. Understanding which speech features support successful perception in noise in NH listeners could provide insight into the difficulty that CI listeners experience in background noise. One set of speech features that has not been thoroughly investigated with regard to its noise immunity is prosody. Existing reports show that CI users have difficulty with prosody perception. The present study endeavoured to determine if prosody is particularly noise-immune in NH listeners and whether the difficulty that CI users experience in noise can be partly explained by poor prosody perception. This was done through the use of three listening experiments.
The first listening experiment examined the noise immunity of prosody in NH listeners by comparing perception of a prosodic pattern to word recognition in speech-weighted noise (SWN). Prosody perception was tested in a two-alternatives forced-choice (2AFC) test paradigm using sentences conveying either conditional or unconditional permission, agreement or approval. Word recognition was measured in an open set test paradigm using meaningful sentences. Results indicated that the deterioration slope of prosody recognition (corrected for guessing) was significantly shallower than that of word recognition. At the lowest signal-to-noise ratio (SNR) tested, prosody recognition was significantly better than word recognition.
The second experiment compared recognition of prosody and phonemes in SWN by testing perception of both in a 2AFC test paradigm. NH and CI listeners were tested using single words as stimuli. Two prosody recognition tasks were used; the first task required discrimination between questions and statements, while the second task required discrimination between a certain and a hesitant attitude. Phoneme recognition was measured with three vowel pairs selected according to specific acoustic cues. Contrary to the first experiment, the results of this experiment indicated that vowel recognition was significantly better than prosody recognition in noise in both listener groups.
The difference between the results of the first and second experiments was thought to have been due to either the test paradigm difference in the first experiment (closed set versus open set), or a difference in stimuli between the experiments (single words versus sentences). The third experiment tested emotional prosody and phoneme perception of NH and CI listeners in SWN using sentence stimuli and a 4AFC test paradigm for both tasks. In NH listeners, deterioration slopes of prosody and phonemes (vowels and consonants) did not differ significantly, and at the lowest SNR tested there was no significant difference in recognition of the different types of speech material. In the CI group, prosody and vowel perception deteriorated with a similar slope, while consonant recognition showed a steeper slope than prosody recognition. It is concluded that while prosody might support speech recognition in noise in NH listeners, explicit recognition of prosodic patterns is not particularly noise-immune and does not account for the difficulty that CI users experience in noise. ## Ontvangers van hedendaagse kogleêre inplantings (KI’s) behaal merkwaardige sukses met spraakherkenning in stilte, maar nie met spraakherkenning in geraas nie. Normaalhorende (NH) luisteraars, aan die ander kant, vaar relatief goed met spraakherkenning in geraas. Begrip van die spraakeienskappe wat suksesvolle persepsie in geraas ondersteun in NH luisteraars, kan lei tot insig in die probleme wat KI-gebruikers in agtergrondgeraas ervaar. Een stel spraakeienskappe wat nog nie deeglik ondersoek is met betrekking tot ruisimmuniteit nie, is prosodie. Bestaande navorsing wys dat KI-gebruikers sukkel met persepsie van prosodie. Die huidige studie is onderneem om te bepaal of prosodie besonder ruisimmuun is in NH luisteraars en of die probleme wat KI-gebruikers in geraas ondervind, deels verklaar kan word deur swak prosodie-persepsie. Dit is gedoen deur middel van drie luistereksperimente.
Die eerste luistereksperiment het die ruisimmuniteit van prosodie in NH luisteraars ondersoek deur die persepsie van ’n prosodiese patroon te vergelyk met woordherkenning in spraakgeweegde ruis (SGR). Prosodie-persepsie is getoets in ’n twee-alternatiewe-gedwonge-keuse- (2AGK) toetsparadigma met sinne wat voorwaardelike of onvoorwaardelike toestemming, instemming of goedkeuring oordra. Woordherkenning is gemeet in ’n oopstel-toetsparadigma met betekenisvolle sinne. Resultate het aangedui dat die helling van agteruitgang van prosodieherkenning (gekorrigeer vir raai) betekenisvol platter was as dié van woordherkenning, en dat by die laagste sein-tot-ruiswaarde (STR) wat getoets is, prosodieherkenning betekenisvol beter was as woordherkenning.
Die tweede eksperiment het prosodie- en foneemherkenning in SGR vergelyk deur die persepsie van beide te toets in ’n 2AGK-toetsparadigma. NH en KI-luisteraars is getoets met enkelwoorde as stimuli. Twee prosodieherkenningstake is gebruik; die eerste taak het diskriminasie tussen vrae en stellings vereis, terwyl die tweede taak diskriminasie tussen ’n seker en onseker houding vereis het. Foneemherkenning is gemeet met drie vokaalpare wat geselekteer is na aanleiding van spesifieke akoestiese eienskappe. In teenstelling met die eerste eksperiment, het resultate van hierdie eksperiment aangedui dat vokaalherkenning betekenisvol beter was as prosodieherkenning in geraas in beide luisteraarsgroepe.
Die verskil tussen die resultate van die eerste en tweede eksperimente kon moontlik die gevolg wees van óf die verskil in toetsparadigma in die eerste eksperiment (geslote- teenoor oop-stel), óf ’n verskil in stimuli tussen die eksperimente (enkelwoorde teenoor sinne). Die derde eksperiment het emosionele-prosodie- en foneempersepsie van NH en KI-luisteraars getoets in SGR met sinstimuli en ’n 4AGK-toetsparadigma vir beide take. In NH luisteraars het die helling van agteruitgang van die persepsie van prosodie en foneme (vokale en konsonante) nie betekenisvol verskil nie, en by die laagste STR wat getoets is, was daar nie ’n betekenisvolle verskil in die herkenning van die twee tipes spraakmateriaal nie. In die KI-groep het prosodie- en vokaalpersepsie met soortgelyke hellings agteruitgegaan, terwyl konsonantherkenning ’n steiler helling as prosodieherkenning vertoon het. Die gevolgtrekking was dat alhoewel prosodie spraakherkenning in geraas in NH luisteraars mag ondersteun, die eksplisiete herkenning van prosodiese patrone nie besonder ruisimmuun is nie en dus nie ’n verklaring bied vir die probleme wat KI-gebruikers in geraas ervaar nie. / Thesis (PhD)--University of Pretoria, 2014. / lk2014 / Electrical, Electronic and Computer Engineering / PhD / unrestricted
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