The concept of statistical significance and the controversy about one-tailed tests.

Hj, Eysenck

doi:10.1037/h0048412

Cited by 46 publications

(40 citation statements)

References 9 publications

(8 reference statements)

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“…In such circumstances a correction of the significance threshold (e. g., the Bonferroni adjustment [146]) would be required; unfortunately, in most of the cases, such adjustment would clearly invalidate any significant difference. On the other hand, already in [67,160] and more recently again in [136], it was suggested to use significance not in the inferential meaning but as a sort of descriptive device. Moreover, there are strong arguments against 'statistical rituals' such as significance testing [80]; effect size/power seem to be more adequate measures [44,71] but have been largely neglected so far.…”

Section: Discussionmentioning

confidence: 99%

Recognising realistic emotions and affect in speech: State of the art and lessons learnt from the first challenge

Schuller

Batliner

Steidl

et al. 2011

Speech Communication

610

329

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More than a decade has passed since research on automatic recognition of emotion from speech has become a new field of research in line with its 'big brothers' speech and speaker recognition. This article attempts to provide a short overview on where we are today, how we got there and what this can reveal us on where to go next and how we could arrive there. In a first part, we address the basic phenomenon reflecting the last fifteen years, commenting on databases, modelling and annotation, the unit of analysis and prototypicality. We then shift to automatic processing including discussions on features, classification, robustness, evaluation, and implementation and system integration. From there we go to the first comparative challenge on emotion recognition from speech -the INTERSPEECH 2009 Emotion Challenge, organised by (part of) the authors, including the description of the Challenge's database, Sub-Challenges, participants and their approaches, the winners, and the fusion of results to the actual learnt lessons before we finally address the ever-lasting problems and future promising attempts.Keywords: emotion, affect, automatic classification, feature types, feature selection, noise robustness, adaptation, standardisation, usability, evaluation Setting the SceneThis special issue will address new approaches towards dealing with the processing of realistic emotions in speech, and this overview article will give an account of the state-of-the-art, of the lacunas in this field, and of promising approaches towards overcoming shortcomings in modelling and recognising realistic emotions. We will also report on the first emotion challenge at INTERSPEECH 2009, constituting the initial impetus of this special issue; to end with, we want to sketch future strategies and applications, trying to answer the question 'Where to go from here?'The article is structured as follows: we first deal with the basic phenomenon briefly reflecting the last fifteen years, commenting on databases, modelling and annotation, the unit of analysis and prototypicality. We then proceed to automatic processing (sec. 2) including discussions on features, classification, robustness, evaluation, and implementation and system integration. From there we go to the the first Emotion Challenge (sec. 3) including the description of the Challenge's database, Sub-Challenges, participants and their approaches, the winners, and the fusion of results to the lessons learnt, before concluding this article (sec. 4).

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Section: Discussionmentioning

confidence: 99%

Recognising realistic emotions and affect in speech: State of the art and lessons learnt from the first challenge

Schuller

Batliner

Steidl

et al. 2011

Speech Communication

610

329

View full text Add to dashboard Cite

show abstract

“…Critique of NHST started not much later (Jeffreys, 1939(Jeffreys, , 1948(Jeffreys, , 1961 and has been forcefully present since then (Jeffreys, 1939(Jeffreys, , 1948(Jeffreys, , 1961Eysenck, 1960;Nunnally, 1960;Rozeboom, 1960;Clark, 1963;Bakan, 1966;Meehl, 1967;Lykken, 1968) and continues to-date (Wasserstein and Lazar, 2016). The problems are numerous, and as Edwards (1972, p. 179) concluded 44 years ago: "any method which invites the contemplation of a null hypothesis is open to grave misuse, or even abuse."…”

Section: The State Of the Art Must Change Nhst Is Unsuitable As The Cmentioning

confidence: 99%

When null hypothesis significance testing is unsuitable for research: a reassessment

Szűcs

Ioannidis

2016

Preprint

107

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Null hypothesis significance testing (NHST) has several shortcomings that are likely contributing factors behind the widely debated replication crisis of (cognitive) neuroscience, psychology, and biomedical science in general. We review these shortcomings and suggest that, after sustained negative experience, NHST should no longer be the default, dominant statistical practice of all biomedical and psychological research. If theoretical predictions are weak we should not rely on all or nothing hypothesis tests. Different inferential methods may be most suitable for different types of research questions. Whenever researchers use NHST they should justify its use, and publish pre-study power calculations and effect sizes, including negative findings. Hypothesis-testing studies should be pre-registered and optimally raw data published. The current statistics lite educational approach for students that has sustained the widespread, spurious use of NHST should be phased out.

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“…In case of p-values above 0.05 and below 0.10, we may speak of weak tendencies, in case of 'significant' values below 0.05, we can assume strong tendencies. However, as we do not claim any 'significance' in its strict meaning, for reasons already discussed by [6], we do not adjust the level of significance for repeated measures; we rather use the p-values reported in a descriptive sense, the same way as the effect size measure phi, indicating strong tendencies that are worthwhile to be pursued further on. 1(a).…”

Section: Resultsmentioning

confidence: 99%

Associating children's non-verbal and verbal behaviour: Body movements, emotions, and laughter in a human-robot interaction

Batliner

Steidl

Nöth

2011

2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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The concept of statistical significance and the controversy about one-tailed tests.

Cited by 46 publications

References 9 publications

Recognising realistic emotions and affect in speech: State of the art and lessons learnt from the first challenge

Recognising realistic emotions and affect in speech: State of the art and lessons learnt from the first challenge

When null hypothesis significance testing is unsuitable for research: a reassessment

Associating children's non-verbal and verbal behaviour: Body movements, emotions, and laughter in a human-robot interaction

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