Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  present our experiments in context-free recognition of non-lexical responses. Non-lexical verbal responses such as mmm-hmm or uh-huh are used by listeners to signal confirmation, uncertainty in understanding, agreement or disagreement in speech-based interaction beten humans. Correct recognition of these utterances by speech interfaces can lead to a more natural interaction paradigm with computers.  present our study on both human and automatic recognition of positive (yes) and negative (no) non-lexical utterances. Approximately 3000 isolated utterances from 26 German native speakers re collected in a human-human spoken interaction setting. Our experiments indicate that human recognition accuracy is close to 99% and up to 90% accuracy can be obtained by standard automatic recognition techniques.
['Shiva Sundaram', 'Robert Schleicher', 'Nathalie Diehl']
I am writing a research paper on a idea Experiments in context-independent recognition of non-lexical ‘yes’ or ‘no’ responses
[{"from": "human", "value": "I am writing a research paper on a idea Experiments in context-independent recognition of non-lexical \u2018yes\u2019 or \u2018no\u2019 responses"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  present our experiments in context-free recognition of non-lexical responses. Non-lexical verbal responses such as mmm-hmm or uh-huh are used by listeners to signal confirmation, uncertainty in understanding, agreement or disagreement in speech-based interaction beten humans. Correct recognition of these utterances by speech interfaces can lead to a more natural interaction paradigm with computers.  present our study on both human and automatic recognition of positive (yes) and negative (no) non-lexical utterances. Approximately 3000 isolated utterances from 26 German native speakers re collected in a human-human spoken interaction setting. Our experiments indicate that human recognition accuracy is close to 99% and up to 90% accuracy can be obtained by standard automatic recognition techniques."}]