摘要:
An apparatus for speech recognition includes: a first confidence score calculator calculating a first confidence score using a ratio between a likelihood of a keyword model for feature vectors per frame of a speech signal and a likelihood of a Filler model for the feature vectors; a second confidence score calculator calculating a second confidence score by comparing a Gaussian distribution trace of the keyword model per frame of the speech signal with a Gaussian distribution trace sample of a stored corresponding keyword of the keyword model; and a determination module determining a confidence of a result using the keyword model in accordance with a position determined by the first and second confidence scores on a confidence coordinate system.
摘要:
An apparatus for speech recognition includes: a first confidence score calculator calculating a first confidence score using a ratio between a likelihood of a keyword model for feature vectors per frame of a speech signal and a likelihood of a Filler model for the feature vectors; a second confidence score calculator calculating a second confidence score by comparing a Gaussian distribution trace of the keyword model per frame of the speech signal with a Gaussian distribution trace sample of a stored corresponding keyword of the keyword model; and a determination module determining a confidence of a result using the keyword model in accordance with a position determined by the first and second confidence scores on a confidence coordinate system.
摘要:
Disclosed herein is a method and apparatus to recognize speech by measuring the confidence levels of respective frames. The method includes the operations of obtaining frequency features of a received speech signal for the respective frames having a predetermined length, calculating a keyword model-based likelihood and a filler model-based likelihood for each of the frame, calculating a confidence score based on the two types of likelihoods, and deciding whether the received speech signal corresponds to a keyword or a non-keyword based on the confidence scores. Also, the method includes the operation of transforming the confidence scores by applying transform functions of clusters, which include the confidence scores or are close to the confidence scores, to the confidence scores.
摘要:
Disclosed herein is a method and apparatus to recognize speech by measuring the confidence levels of respective frames. The method includes the operations of obtaining frequency features of a received speech signal for the respective frames having a predetermined length, calculating a keyword model-based likelihood and a filler model-based likelihood for each of the frame, calculating a confidence score based on the two types of likelihoods, and deciding whether the received speech signal corresponds to a keyword or a non-keyword based on the confidence scores. Also, the method includes the operation of transforming the confidence scores by applying transform functions of clusters, which include the confidence scores or are close to the confidence scores, to the confidence scores.
摘要:
Provided is a method and apparatus for transforming a speech feature vector. The method includes extracting a feature vector required for speech recognition from a speech signal and transforming the extracted feature vector using an auto-associative neural network (AANN).
摘要:
Provided are a multi-stage speech recognition apparatus and method. The multi-stage speech recognition apparatus includes a first speech recognition unit performing initial speech recognition on a feature vector, which is extracted from an input speech signal, and generating a plurality of candidate words; and a second speech recognition unit rescoring the candidate words, which are provided by the first speech recognition unit, using a temporal posterior feature vector extracted from the speech signal.
摘要:
An audio apparatus including a decorrelator for generating decorrelated signals by applying a phase shifting value adjusted based on a correlation difference between audio signals included in a multi-channel signal to the audio signals; and a speaker set including at least two speakers for outputting acoustic signals corresponding to the decorrelated signals.
摘要:
Provided is a method and apparatus for transforming a speech feature vector. The method includes extracting a feature vector required for speech recognition from a speech signal and transforming the extracted feature vector using an auto-associative neural network (AANN).
摘要:
Provided are a multi-stage speech recognition apparatus and method. The multi-stage speech recognition apparatus includes a first speech recognition unit performing initial speech recognition on a feature vector, which is extracted from an input speech signal, and generating a plurality of candidate words; and a second speech recognition unit rescoring the candidate words, which are provided by the first speech recognition unit, using a temporal posterior feature vector extracted from the speech signal.
摘要:
Provided is a sound source signal filtering method and apparatus. The sound source signal filtering method includes: generating two or more microphone output signals by combining sound source signals input through a plurality of microphones; calculating distances between the microphones and a sound source from which the sound source signals are emitted by using distance relationships according to frequencies of the sound source signals extracted from the generated microphone output signals; and filtering the sound source signals to obtain one or more sound source signals corresponding to a predetermined distance by using the calculated distances. Accordingly, it is possible to obtain only sound source signals emitted from a sound source at a particular distance from the microphone array among a plurality of sound source signals input through the microphone array.