Evaluating Speech-in-Speech Perception via a Humanoid Robot
December 19, 2023 Β· Declared Dead Β· π Frontiers in Neuroscience
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Luke Meyer, Gloria Araiza-Illan, Laura Rachman, Etienne Gaudrain, Deniz Baskent
arXiv ID
2312.12262
Category
eess.AS: Audio & Speech
Cross-listed
cs.RO,
cs.SD
Citations
2
Venue
Frontiers in Neuroscience
Last Checked
3 months ago
Abstract
Underlying mechanisms of speech perception masked by background speakers, a common daily listening condition, are often investigated using various and lengthy psychophysical tests. The presence of a social agent, such as an interactive humanoid NAO robot, may help maintain engagement and attention. However, such robots potentially have limited sound quality or processing speed. As a first step towards the use of NAO in psychophysical testing of speech-in-speech perception, we compared normal-hearing young adults' performance when using the standard computer interface to that when using a NAO robot to introduce the test and present all corresponding stimuli. Target sentences were presented with colour and number keywords in the presence of competing masker speech at varying target-to-masker ratios. Sentences were produced by the same speaker, but voice differences between the target and masker were introduced using speech synthesis methods. To assess test performance, speech intelligibility and data collection duration were compared between the computer and NAO setups. Human-robot interaction was assessed using the Negative Attitude Towards Robot Scale (NARS) and quantification of behavioural cues (backchannels). Speech intelligibility results showed functional similarity between the computer and NAO setups. Data collection durations were longer when using NAO. NARS results showed participants had a more positive attitude toward robots prior to their interaction with NAO. The presence of more positive backchannels when using NAO suggest higher engagement with the robot in comparison to the computer. Overall, the study presents the potential of the NAO for presentingspeech materials and collecting psychophysical measurements for speech-in-speech perception.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Audio & Speech
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
LPCNet: Improving Neural Speech Synthesis Through Linear Prediction
R.I.P.
π»
Ghosted
VoiceFilter: Targeted Voice Separation by Speaker-Conditioned Spectrogram Masking
R.I.P.
π»
Ghosted
TERA: Self-Supervised Learning of Transformer Encoder Representation for Speech
R.I.P.
π»
Ghosted
Mockingjay: Unsupervised Speech Representation Learning with Deep Bidirectional Transformer Encoders
R.I.P.
π»
Ghosted
Utterance-level Aggregation For Speaker Recognition In The Wild
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted