Patent Document ID: 8160866
Application ID: 12248924

Base Claim:
1. A speech recognition method for both English and Chinese provides both English word, sentence, name, and Chinese syllable, sentence, name recognition comprising: (1). providing an English word and Chinese syllable database, a English and Chinese sentence and name database and deleting noise and the time interval without speech signal by using a processor; (2). normalizing the whole speech waveform of a known English word (Chinese syllable) by using E=12 elastic frames without filter and without overlap and transforming the waveform into an E×P=12×12 matrix of linear predictive coding cepstra (LPCC) such that the same English words (Chinese syllables) have about the same LPCC at the same time position in their E×P=12×12 matrices of LPCC; (3). wherein from all samples of each known English word (Chinese syllable), select its best K samples to compute the feature to represent the known English word (Chinese syllable); (4). wherein the best K samples of a known English word (Chinese syllable) are used to compute the means and all samples of the known English word (Chinese syllable) are used to compute the variances of LPCC and the E×P=12×12 matrix of means and variances is called the standard pattern to represent the feature of the known English word (Chinese syllable) and is saved in the English word and Chinese syllable database; (5). normalizing the whole waveform of an input unknown English word (Chinese syllable) by using E=12 elastic frames without filter and without overlap and transforming the waveform into an E×P=12×12 matrix of linear predict coding cepstra (LPCC), which is called the categorizing pattern to represent the unknown English word (Chinese syllable); (6). wherein a simplified Bayesian decision classifier is used to match the standard pattern of every known English word (Chinese syllable) with the categorizing pattern of an input unknown English word (Chinese syllable) and to find a known English word (Chinese syllable) with the least Bayesian distance to be the unknown English word (Chinese syllable); (7). modifying and improving the feature of an English word (Chinese syllable) such that the English word (Chinese syllable) is guaranteed to be recognized correctly, and creating the feature (standard pattern) of a new English word and a new Chinese syllable; (8). partitioning an unknown English (Chinese) sentence or name into D unknown English words (D unknown Chinese syllables); (9). wherein a simplified Bayesian classifier to find the F most similar known English words or Chinese syllables or both from the English word and Chinese syllable database for each of D unknown English words (Chinese syllables) and representing an unknown English (Chinese) sentence or name by using a D×F matrix of known similar English words or Chinese syllables or both; (10). wherein the D×F matrix of similar known English words (Chinese syllables) is used to matches all known English (Chinese) sentences and names in the English and Chinese sentence and name database and find a known English (Chinese) sentence or name with the highest probability to be the unknown sentence or name; (11). modifying and improving the feature of an unknown English word (Chinese syllable) in the input unknown English (Chinese) sentence or name such that the input unknown sentence or name is guaranteed to be recognized correctly; and (12). since the features of English words (without samples) are created from the features of Chinese syllables, performing speech recognition on other languages, such as German, French, Japanese, Korean, and Russian, wherein the features of said other languages can be created from the features of Chinese syllables to perform said speech recognition.

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Claim 10:
10. The speech recognition method for both English and Chinese as claimed in claim 1 , wherein said step (10) further includes recognizing the unknown English or Chinese sentence or name: (a). selecting the matching English or Chinese sentence or name with D−1, D and D+1 known English words or known Chinese syllables in the English and Chinese sentence and name database; (b). if the matching known sentence or name just has D words or syllables, then comparing in row order, each of D rows of the F most similar known words (syllables) with each of known words (syllables) in the matching sentence or name; (c). if each row of similar known words (syllables) contains a known word (syllable) in the matching sentence or name, then D unknown English words or D unknown Chinese syllables being recognized correctly and deciding the matching sentence or name to be the unknown sentence or name; (d). if in (c), the number of correctly recognized words (syllables) is not D or if the matching sentence or name contains D−1 or D+1 known words (syllables), using 3×F window (3 consecutive rows of similar words (syllables)) to screen each known word (syllable) of the matching sentence or name, using the (i−1)-th, i-th, (i+1)-th rows of F similar known words or syllables to compare with the i-th known word or syllable in the matching sentence or name, using the first two rows of F similar words or syllables to compare with the first known word or syllable in the matching sentence or name, moving the 3×F screen window moves from the first to the last known word (syllable) in the matching sentence or name, and counting the number of the known words (syllables) of the matching sentence or name in the 3×F window; and (e). deciding the matching sentence or name with the highest probability (the number of known words (syllables) of the matching sentence or name in the 3×F window divided by the total number of words (syllables) in the matching sentence or name) to be the unknown sentence or name.