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Found 9 papers, 0 papers with code
Adapting the NICT-JLE Corpus for Disfluency Detection Models
The detection of disfluencies such as hesitations, repetitions and false starts commonly found in speech is a widely studied area of research.
Local Minima Drive Communications in Cooperative Interaction
An important open question in human-robot interaction (HRI) is precisely when an agent should decide to communicate, particularly in a cooperative task.
Whither the Priors for (Vocal) Interactivity?
This is evidenced not only by the fact that contemporary spoken language systems already require training data sets that are orders-of-magnitude greater than that experienced by a young child, but also by the lack of design principles for creating effective communicative human-robot interaction.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Talking with Robots: Opportunities and Challenges
Notwithstanding the tremendous progress that is taking place in spoken language technology, effective speech-based human-robot interaction still raises a number of important challenges.
Vocal Interactivity in Crowds, Flocks and Swarms: Implications for Voice User Interfaces
Recent years have seen an explosion in the availability of Voice User Interfaces.
On the Use/Misuse of the Term 'Phoneme'
The term 'phoneme' lies at the heart of speech science and technology, and yet it is not clear that the research community fully appreciates its meaning and implications.
Automatic recognition of child speech for robotic applications in noisy environments
Automatic speech recognition (ASR) allows a natural and intuitive interface for robotic educational applications for children.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Is spoken language all-or-nothing? Implications for future speech-based human-machine interaction
The answer, based on contemporary views on the special nature of (spoken) language, is that there may indeed be a fundamental limit to the interaction that can take place between mismatched interlocutors (such as humans and machines).
Towards capturing fine phonetic variation in speech using articulatory features
As part of this work we are investigating automatic feature classifiers that are able to create reliable and accurate transcriptions of the articulatory behaviour encoded in the acoustic speech signal.
