METHOD AND SYSTEM FOR AUTOMATICALLY DETECTING MORPHEMES IN A TASK CLASSIFICATION SYSTEM USING LATTICES
The invention concerns a method and system for detecting morphemes in a user's communication. The method may include recognizing a lattice of phone strings from the user's input communication, the lattice representing a distribution over the phone strings, and detecting morphemes in the user's input communication using the lattice. The morphemes may be acoustic and/or non-acoustic. The morphemes may represent any unit or sub-unit of communication including phones, diphones, phone-phrases, syllables, grammars, words, gestures, tablet strokes, body movements, mouse clicks, etc. The training speech may be verbal, non-verbal, a combination of verbal and non-verbal, or multimodal.
1 . A method for detecting morphemes in a user's input communication, comprising:
forming a lattice representing a distribution of acoustic and non-acoustic phone strings associated with morphemes in the user's acoustic and non-acoustic input; and
detecting acoustic and non-acoustic morphemes in the formed lattice.
2 . The method of claim 1 , wherein detecting the acoustic and non-acoustic morphemes further comprises extracting the N-best phone strings from the formal lattice.
3 . The method of claim 1 , wherein detecting the acoustic and non-acoustic morphemes further comprises extracting the N-best phone strings and their confidence scores from the formal lattice.
4 . The method of claim 1 , wherein the non-acoustic communication includes use of at least one of gestures, body movements, head movements, non-responses, text, keyboard entries, keypad entries, mouse clicks, DTMF codes, pointers, stylus, cable set-top box entries, graphical user interface entries and touchscreen entries.
5 . The method of claim 1 , wherein the user's input communication is in multimodal form.
6 . The method of claim 1 , wherein the user's acoustic input is verbal.
7 . The method of claim 1 , wherein detecting acoustic and non-acoustic morphemes is performed using morphemes from a morpheme generation subsystem.
8 . The method of claim 1 , further comprising:
providing the detected acoustic and non-acoustic morphemes to a task classification processor.
9 . The method of claim 8 , further comprising:
based on a probabilistic relationship, implementing a task objective between the detected morphemes and selected task objectives.
10 . A system for detecting morphemes in a user's input communication, the system comprising:
a module configured to form a lattice representing a distribution of acoustic and non-acoustic phone strings associated with morphemes in the user's acoustic and non-acoustic input; and
a module configured to detect acoustic and non-acoustic morphemes in the formed lattice.
11 . The system of claim 10 , wherein detecting the acoustic and non-acoustic morphemes further comprises a module configured to extract the N-best phone strings from the formal lattice.
12 . The system of claim 10 , wherein detecting the acoustic and non-acoustic morphemes further comprises a module configured to extract the N-best phone strings and their confidence scores from the formal lattice.
13 . The system of claim 10 , wherein the non-acoustic communication includes use of at least one of gestures, body movements, head movements, non-responses, text, keyboard entries, keypad entries, mouse clicks, DTMF codes, pointers, stylus, cable set-top box entries, graphical user interface entries and touchscreen entries.
14 . The system of claim 10 , wherein the user's input communication is in multimodal form.
15 . The system of claim 10 , wherein the user's acoustic input is verbal.
16 . The system of claim 10 , wherein detecting acoustic and non-acoustic morphemes is performed using morphemes from a morpheme generation subsystem.
17 . The system of claim 10 , further comprising:
a module configured to provide the detected acoustic and non-acoustic morphemes to a task classification processor.
18 . The system of claim 17 , further comprising:
a module configured to implement a task objective between the detected morphemes and selected task objectives and based on a probabilistic relationship.
19 . A computer readable medium storing instructions for controlling a computing device to detect morphemes in a user's input communication, the instructions comprising:
forming a lattice representing a distribution of acoustic and non-acoustic phone strings associated with morphemes in the user's acoustic and non-acoustic input; and
detecting acoustic and non-acoustic morphemes in the formed lattice.
20 . The computer readable medium of claim 19 , wherein detecting the acoustic and non-acoustic morphemes further comprises extracting the N-best phone strings from the formal lattice.
21 . The computer readable medium of claim 19 , wherein detecting the acoustic and non-acoustic morphemes further comprises extracting the N-best phone strings and their confidence scores from the formal lattice.
22 . The computer readable medium of claim 19 , wherein the non-acoustic communication includes use of at least one of gestures, body movements, head movements, non-responses, text, keyboard entries, keypad entries, mouse clicks, DTMF codes, pointers, stylus, cable set-top box entries, graphical user interface entries and touchscreen entries.
23 . The computer readable medium of claim 19 , wherein the user's input communication is in multimodal form.
24 . The computer readable medium of claim 19 , wherein the user's acoustic input is verbal.
25 . The computer readable medium of claim 19 , wherein detecting acoustic and non-acoustic morphemes is performed using morphemes from a morpheme generation subsystem.