Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:   present a novel approach to acoustic model training for non-audible murmur (NAM) recognition using normal speech data transformed into NAM data. NAM is extremely soft murmur, that is so quiet that people around the speaker can hardly hear it. It is detected directly through the soft tissue of the head using a special body-conductive microphone, NAM microphone, placed on the neck below the ear. NAM recognition is one of the promising silent speech interfaces for man-machine speech communication.  have previously shown the effectiveness of speaker adaptive training (SAT) based on constrained maximum likelihood linear regression (CMLLR) in NAM acoustic model training. Hover, since the amount of available NAM data is still small, the effect of SAT is limited.   propose modified SAT methods capable of using a larger amount of normal speech data by transforming them into NAM data. The experimental results demonstrate that the proposed methods yield an absolute increase of approximately 2% in word accuracy compared with the conventional method.
['Denis Babani', 'Tomoki Toda', 'Hiroshi Saruwatari', 'Kiyohiro Shikano']
I am writing a research paper on a idea Acoustic model training for non-audible murmur recognition using transformed normal speech data
[{"from": "human", "value": "I am writing a research paper on a idea Acoustic model training for non-audible murmur recognition using transformed normal speech data"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:   present a novel approach to acoustic model training for non-audible murmur (NAM) recognition using normal speech data transformed into NAM data. NAM is extremely soft murmur, that is so quiet that people around the speaker can hardly hear it. It is detected directly through the soft tissue of the head using a special body-conductive microphone, NAM microphone, placed on the neck below the ear. NAM recognition is one of the promising silent speech interfaces for man-machine speech communication.  have previously shown the effectiveness of speaker adaptive training (SAT) based on constrained maximum likelihood linear regression (CMLLR) in NAM acoustic model training. Hover, since the amount of available NAM data is still small, the effect of SAT is limited.   propose modified SAT methods capable of using a larger amount of normal speech data by transforming them into NAM data. The experimental results demonstrate that the proposed methods yield an absolute increase of approximately 2% in word accuracy compared with the conventional method."}]