Publications

Abstract

In face-to-face conversation, people use speech and gesture to convey meaning. Seeing gestures alongside speech facilitates comprehenders’ language processing, but crucially, the mechanisms underlying this facilitation remain unclear. We investigated whether comprehenders use the semantic information in gestures, typically preceding related speech, to predict upcoming meaning. Dutch adults listened to questions asked by a virtual avatar. Questions were accompanied by an iconic gesture (e.g., typing) or meaningless control movement (e.g., arm scratch) followed by a short pause and target word (e.g., “type”). A Cloze experiment showed that gestures improved explicit predictions of upcoming target words. Moreover, an EEG experiment showed that gestures reduced alpha and beta power during the pause, indicating anticipation, and reduced N400 amplitudes, demonstrating facilitated semantic processing. Thus, comprehenders use iconic gestures to predict upcoming meaning. Theories of linguistic prediction should incorporate communicative bodily signals as predictive cues to capture how language is processed in face-to-face interaction.

Abstract

Native listeners benefit from both visible speech and iconic gestures to enhance degraded speech comprehension (Drijvers & Ozyürek, 2017). We tested how highly proficient non-native listeners benefit from these visual articulators compared to native listeners. We presented videos of an actress uttering a verb in clear, moderately, or severely degraded speech, while her lips were blurred, visible, or visible and accompanied by a gesture. Our results revealed that unlike native listeners, non-native listeners were less likely to benefit from the combined enhancement of visible speech and gestures, especially since the benefit from visible speech was minimal when the signal quality was not sufficient.

Abstract

In human face-to-face communication, speech is frequently accompanied by visual signals, especially communicative hand gestures. Analyzing these visual signals requires detailed manual annotation of video data, which is often a labor-intensive and time-consuming process. To facilitate this process, we here present SPUDNIG (SPeeding Up the Detection of Non-iconic and Iconic Gestures), a tool to automatize the detection and annotation of hand movements in video data. We provide a detailed description of how SPUDNIG detects hand movement initiation and termination, as well as open-source code and a short tutorial on an easy-to-use graphical user interface (GUI) of our tool. We then provide a proof-of-principle and validation of our method by comparing SPUDNIG’s output to manual annotations of gestures by a human coder. While the tool does not entirely eliminate the need of a human coder (e.g., for false positives detection), our results demonstrate that SPUDNIG can detect both iconic and non-iconic gestures with very high accuracy, and could successfully detect all iconic gestures in our validation dataset. Importantly, SPUDNIG’s output can directly be imported into commonly used annotation tools such as ELAN and ANVIL. We therefore believe that SPUDNIG will be highly relevant for researchers studying multimodal communication due to its annotations significantly accelerating the analysis of large video corpora.

Abstract

In face-to-face conversation, recipients might use the bodily movements of the speaker (e.g. gestures) to facilitate language processing. It has been suggested that one way through which this facilitation may happen is prediction. However, for this to be possible, gestures would need to precede speech, and it is unclear whether this is true during natural conversation.
In a corpus of Dutch conversations, we annotated hand gestures that represent semantic information and occurred during questions, and the word(s) which corresponded most closely to the gesturally depicted meaning. Thus, we tested whether representational gestures temporally precede their lexical affiliates. Further, to see whether preceding gestures may indeed facilitate language processing, we asked whether the gesture-speech asynchrony predicts the response time to the question the gesture is part of.
Gestures and their strokes (most meaningful movement component) indeed preceded the corresponding lexical information, thus demonstrating their predictive potential. However, while questions with gestures got faster responses than questions without, there was no evidence that questions with larger gesture-speech asynchronies get faster responses. These results suggest that gestures indeed have the potential to facilitate predictive language processing, but further analyses on larger datasets are needed to test for links between asynchrony and processing advantages.

Abstract

A commentary on
Transcranial Magnetic Stimulation over Left Inferior Frontal and Posterior Temporal Cortex Disrupts Gesture-Speech Integration

by Zhao, W., Riggs, K., Schindler, I., and Holle, H. (2018). J. Neurosci. 10, 1748–1717. doi: 10.1523/JNEUROSCI.1748-17.2017

Abstract

Previous work revealed that visual semantic information conveyed by gestures can enhance degraded speech comprehension, but the mechanisms underlying these integration processes under adverse listening conditions remain poorly understood. We used MEG to investigate how oscillatory dynamics support speech–gesture integration when integration load is manipulated by auditory (e.g., speech degradation) and visual semantic (e.g., gesture congruency) factors. Participants were presented with videos of an actress uttering an action verb in clear or degraded speech, accompanied by a matching (mixing gesture + “mixing”) or mismatching (drinking gesture + “walking”) gesture. In clear speech, alpha/beta power was more suppressed in the left inferior frontal gyrus and motor and visual cortices when integration load increased in response to mismatching versus matching gestures. In degraded speech, beta power was less suppressed over posterior STS and medial temporal lobe for mismatching compared with matching gestures, showing that integration load was lowest when speech was degraded and mismatching gestures could not be integrated and disambiguate the degraded signal. Our results thus provide novel insights on how low-frequency oscillatory modulations in different parts of the cortex support the semantic audiovisual integration of gestures in clear and degraded speech: When speech is clear, the left inferior frontal gyrus and motor and visual cortices engage because higher-level semantic information increases semantic integration load. When speech is degraded, posterior STS/middle temporal gyrus and medial temporal lobe are less engaged because integration load is lowest when visual semantic information does not aid lexical retrieval and speech and gestures cannot be integrated.

Abstract

During face-to-face communication, listeners integrate speech with gestures. The semantic information conveyed by iconic gestures (e.g., a drinking gesture) can aid speech comprehension in adverse listening conditions. In this magnetoencephalography (MEG) study, we investigated the spatiotemporal neural oscillatory activity associated with gestural enhancement of degraded speech comprehension. Participants watched videos of an actress uttering clear or degraded speech, accompanied by a gesture or not and completed a cued-recall task after watching every video. When gestures semantically disambiguated degraded speech comprehension, an alpha and beta power suppression and a gamma power increase revealed engagement and active processing in the hand-area of the motor cortex, the extended language network (LIFG/pSTS/STG/MTG), medial temporal lobe, and occipital regions. These observed low- and high-frequency oscillatory modulations in these areas support general unification, integration and lexical access processes during online language comprehension, and simulation of and increased visual attention to manual gestures over time. All individual oscillatory power modulations associated with gestural enhancement of degraded speech comprehension predicted a listener's correct disambiguation of the degraded verb after watching the videos. Our results thus go beyond the previously proposed role of oscillatory dynamics in unimodal degraded speech comprehension and provide first evidence for the role of low- and high-frequency oscillations in predicting the integration of auditory and visual information at a semantic level.

Abstract

Native listeners neurally integrate iconic gestures with speech, which can enhance degraded speech comprehension. However, it is unknown how non-native listeners neurally integrate speech and gestures, as they might process visual semantic context differently than natives. We recorded EEG while native and highly-proficient non-native listeners watched videos of an actress uttering an action verb in clear or degraded speech, accompanied by a matching ('to drive'+driving gesture) or mismatching gesture ('to drink'+mixing gesture). Degraded speech elicited an enhanced N400 amplitude compared to clear speech in both groups, revealing an increase in neural resources needed to resolve the spoken input. A larger N400 effect was found in clear speech for non-natives compared to natives, but in degraded speech only for natives. Non-native listeners might thus process gesture more strongly than natives when speech is clear, but need more auditory cues to facilitate access to gestural semantic information when speech is degraded.