Abstract: A noise suppression circuit for use in an audio signal processing circuit is provided. The noise suppression circuit includes a plurality of different types of noise activity detectors, which are each adapted for detecting the presence of a different type of noise in a received signal. The noise suppression circuit further includes a plurality of different types of noise reduction circuits, which are each adapted for removing a different type of detected noise, where each noise reduction circuit respectively corresponds to one of the plurality of noise activity detectors. The respective noise reduction circuit is then selectively activated to condition the received signal to reduce the amount of the detected types of noise, when each one of the plurality of noise activity detectors detects the presence of a corresponding type of noise in the received signal.

Abstract: A method (400, 500) and apparatus (220) seeks to improve the intelligibility of speech emitted into a noisy environment. Formants are identified (426) and perceptual frequency scale band is selected (502) that includes at least one of the identified formants. The SNR in each band is compared (504) to a threshold and, if the SNR for that band is less than the threshold, the method increases a formant enhancement gain for that band. A set of high pass filter gains (338) is combined (516) with the formant enhancement gains yielding combined gains that are then clipped (518), scaled (520) according to a total SNR, normalized (526), smoothed across time (530) and frequency (532), and used to reconstruct (532, 534) an audio signal.

Abstract: A method (400, 500) and apparatus (220) seeks to improve the intelligibility of speech emitted into a noisy environment. Formants are identified (426) and perceptual frequency scale band is selected (502) that includes at least one of the identified formants. The SNR in each band is compared (504) to a threshold and, if the SNR for that band is less than the threshold, the method increases a formant enhancement gain for that band. A set of high pass filter gains (338) is combined (516) with the formant enhancement gains yielding combined gains that are then clipped (518), scaled (520) according to a total SNR, normalized (526), smoothed across time (530) and frequency (532), and used to reconstruct (532, 534) an audio signal.

Abstract: A method (400, 600, 700) and apparatus (220) for enhancing the intelligibility of speech emitted into a noisy environment. After filtering (408) ambient noise with a filter (304) that simulates the physical blocking of noise by a at least a part of a voice communication device (102) a frequency dependent SNR of received voice audio relative to ambient noise is computed (424) on a perceptual (e.g. Bark) frequency scale. Formants are identified (426, 600, 700) and the SNR in bands including certain formants are modified (508, 510) with formant enhancement gain factors in order to improve intelligibility. A set of high pass filter gains (338) is combined (516) with the formant enhancement gains factors yielding combined gains which are clipped (518), scaled (520) according to a total SNR, normalized (526), smoothed across time (530) and frequency (532) and used to reconstruct (532, 534) an audio signal.

Abstract: A device (800) performs statistical pattern recognition using model parameters that are refined by optimizing an objective function that includes a term for many items of training data for which recognition errors occur wherein each term depends on a relative magnitude of a first score for a recognition result for an item of training data and a second score calculated by evaluating a statistical pattern recognition model identified by a transcribed identity of the training data item with feature vectors extracted from the item of training data. The objective function does not include terms for items of training data for which there is a gross discrepancy between a transcribed identity and a recognized identity. Gross discrepancies can be detected by probability score or pattern identity comparisons. Terms, of the objective function are weighted based on the type of recognition error and weights can be increased for high priority patterns.

Abstract: A system (100) and method (400) for configuring audio processing paths and subsequent data transmission method and link for voice recognition is provided. The system can include a headset (110) to determine a voice request type of a voice signal, configure an audio processing path of the voice signal in accordance with the voice request type, and a mobile device (160) to receive the voice request type and configure an audio processing path and data transmission of the voice signal in accordance with the voice request type for the purpose of achieving a high recognition accuracy with use of a Bluetooth headset in a hands-free mode.

Abstract: A noise suppression circuit for use in an audio signal processing circuit is provided. The noise suppression circuit includes a plurality of different types of noise activity detectors, which are each adapted for detecting the presence of a different type of noise in a received signal. The noise suppression circuit further includes a plurality of different types of noise reduction circuits, which are each adapted for removing a different type of detected noise, where each noise reduction circuit respectively corresponds to one of the plurality of noise activity detectors. The respective noise reduction circuit is then selectively activated to condition the received signal to reduce the amount of the detected types of noise, when each one of the plurality of noise activity detectors detects the presence of a corresponding type of noise in the received signal.