Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: An acoustic confidence measure for acceptance/rejection of recognition hypotheses for continuous speech utterances is proposed. This measure is useful for rejecting utterances that are out of domain, or contain out-of-vocabulary words or speech disfluencies. A phone-based approach is implemented so that a single global threshold can be applied to hypothesis rejection for any word sequence. Phone confidence is computed for each frame of speech as the posterior phone probability given the acoustic observation. Word sequence confidence is evaluated as the average phone confidence, either by ighting all frames equally or by normalizing by phone duration. The confidence measure is tested on a database of spoken company names. When normalized by phone duration, it achieves, in some cases with less computational expense, rejection performance comparable to a baseline system implementing a common filler-model approach. When all frames are equally ighted, performance is substantially poorer.
['Zeév Rivlin', 'Michael A. Cohen', 'Victor Abrash', 'Thomas D. Y. Chung']
I am writing a research paper on a idea A phone-dependent confidence measure for utterance rejection
[{"from": "human", "value": "I am writing a research paper on a idea A phone-dependent confidence measure for utterance rejection"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: An acoustic confidence measure for acceptance/rejection of recognition hypotheses for continuous speech utterances is proposed. This measure is useful for rejecting utterances that are out of domain, or contain out-of-vocabulary words or speech disfluencies. A phone-based approach is implemented so that a single global threshold can be applied to hypothesis rejection for any word sequence. Phone confidence is computed for each frame of speech as the posterior phone probability given the acoustic observation. Word sequence confidence is evaluated as the average phone confidence, either by ighting all frames equally or by normalizing by phone duration. The confidence measure is tested on a database of spoken company names. When normalized by phone duration, it achieves, in some cases with less computational expense, rejection performance comparable to a baseline system implementing a common filler-model approach. When all frames are equally ighted, performance is substantially poorer."}]