Abstract: A speech recognition system and method thereof are provided. The speech recognition system connects to an external general-purpose speech recognition system, and including a storage unit and a processing unit. The storage unit stores a specific application speech recognition module, a comparison module and an enhancement module. The specific application speech recognition module converts a speech signal into a first phonetic text. The general-purpose speech recognition system converts the speech signal into a written text. The comparison module receives the first phonetic text and the written text, converts the written text into a second phonetic text, and aligns the second phonetic text with the first phonetic text according to similarity of pronunciation to output a phonetic text alignment result. The enhancement module receives the phonetic text alignment result, and constructs with the written text and the first phonetic text after path weighting to form an outputting recognized text.

Abstract: A speech recognition system and method thereof are provided. The speech recognition system connects to an external general-purpose speech recognition system, and including a storage unit and a processing unit. The storage unit stores a specific application speech recognition module, a comparison module and an enhancement module. The specific application speech recognition module converts a speech signal into a first phonetic text. The general-purpose speech recognition system converts the speech signal into a written text. The comparison module receives the first phonetic text and the written text, converts the written text into a second phonetic text, and aligns the second phonetic text with the first phonetic text according to similarity of pronunciation to output a phonetic text alignment result. The enhancement module receives the phonetic text alignment result, and constructs with the written text and the first phonetic text after path weighting to form an outputting recognized text.

Abstract: A recognition network generation device, disposed in an electronic device, comprising: an operation record storage device storing a plurality of operation records of the electronic device, wherein each of the operation records includes operation content executed by the electronic device and device peripheral information detected by the electronic device when the electronic device executes the operation content; an activity model constructor classifying the operation records into a plurality of activity models according to all the device peripheral information of the operation records; an activity predictor selecting at least one selected activity model according to the degree of similarity between each of the activity models and a current device peripheral information detected by the electronic device; and a weight adjustor adjusting the weights of a plurality of recognition vocabularies by taking into account a number of times each recognition vocabulary appears in all operations contents of the activity mod

Abstract: A recognition network generation device, disposed in an electronic device, comprising: an operation record storage device storing a plurality of operation records of the electronic device, wherein each of the operation records includes operation content executed by the electronic device and device peripheral information detected by the electronic device when the electronic device executes the operation content; an activity model constructor classifying the operation records into a plurality of activity models according to all the device peripheral information of the operation records; an activity predictor selecting at least one selected activity model according to the degree of similarity between each of the activity models and a current device peripheral information detected by the electronic device; and a weight adjustor adjusting the weights of a plurality of recognition vocabularies, wherein the recognition vocabularies correspond to all the operation content of the at least one selected activity model.

Abstract: A language learning system including a storage module, a feature extraction module, and an assessment and diagnosis module is provided. The storage module stores training data and an assessment decision tree generated according to the training data. The feature extraction module extracts pronunciation features of a pronunciation given by a language learner. The assessment and diagnosis module identifies a diagnosis path corresponding to the pronunciation of the language learner in the assessment decision tree and outputs feedback information corresponding to the diagnosis path. Thereby, the language learning system can assess and provide feedback information regarding words, phrases or sentences pronounced by the language learner.

Abstract: A language learning system including a storage module, a feature extraction module, and an assessment and diagnosis module is provided. The storage module stores training data and an assessment decision tree generated according to the training data. The feature extraction module extracts pronunciation features of a pronunciation given by a language learner. The assessment and diagnosis module identifies a diagnosis path corresponding to the pronunciation of the language learner in the assessment decision tree and outputs feedback information corresponding to the diagnosis path. Thereby, the language learning system can assess and provide feedback information regarding words, phrases or sentences pronounced by the language learner.

Abstract: A method of generating and detecting confusing phones/syllables is disclosed. The method includes a generating stage and a detecting stage. The generating stage includes: (a) input a Mandarin utterance; (b) partition the Mandarin utterance into segmented phones/syllables and generate the most likely route in a recognition net via Forced Alignment of Viterbi decoding; (c) compare the segmented phones/syllables with a Mandarin acoustic model; (d) determine whether a confusing phone/syllable exists; (e) add the confusing phone/syllable into the recognition net and repeat step (b), (c), and (d) when the confusing phone/syllable exists; (f) stop and output all generated confusing phones/syllables to a confusing phone/syllable file when a confusing phone/syllable does not exist.

Abstract: A method of generating and detecting confusing phones/syllables is disclosed. The method includes a generating stage and a detecting stage. The generating stage includes: (a) input a Mandarin utterance; (b) partition the Mandarin utterance into segmented phones/syllables and generate the most likely route in a recognition net via Forced Alignment of Viterbi decoding; (c) compare the segmented phones/syllables with a Mandarin acoustic model; (d) determine whether a confusing phone/syllable exists; (e) add the confusing phone/syllable into the recognition net and repeat step (b), (c), and (d) when the confusing phone/syllable exists; (f) stop and output all generated confusing phones/syllables to a confusing phone/syllable file when a confusing phone/syllable does not exist.