Abstract: Described herein are systems and methods to identify and address sources of bias in an end-to-end speech model. In one or more embodiments, the end-to-end model may be a recurrent neural network with two 2D-convolutional input layers, followed by multiple bidirectional recurrent layers and one fully connected layer before a softmax layer. In one or more embodiments, the network is trained end-to-end using the CTC loss function to directly predict sequences of characters from log spectrograms of audio. With optimized recurrent layers and training together with alignment information, some unwanted bias induced by using purely forward only recurrences may be removed in a deployed model.

Abstract: Described herein are systems and methods to identify and address sources of bias in an end-to-end speech model. In one or more embodiments, the end-to-end model may be a recurrent neural network with two 2D-convolutional input layers, followed by multiple bidirectional recurrent layers and one fully connected layer before a softmax layer. In one or more embodiments, the network is trained end-to-end using the CTC loss function to directly predict sequences of characters from log spectrograms of audio. With optimized recurrent layers and training together with alignment information, some unwanted bias induced by using purely forward only recurrences may be removed in a deployed model.

Abstract: A system for hearing assistance devices to assist hearing aid fitting applied to individual differences in hearing impairment. The system is also usable for assisting fitting and use of hearing assistance devices for listeners of music. The method uses a subjective space approach to reduce the dimensionality of the fitting problem and a non-linear regression technology to interpolate among hearing aid parameter settings. This listener-driven method provides not only a technique for preferred aid fitting, but also information on individual differences and the effects of gain compensation on different musical styles.

Abstract: A system for hearing assistance devices to assist hearing aid fitting applied to individual differences in hearing impairment. The system is also usable for assisting fitting and use of hearing assistance devices for listeners of music. The method uses a subjective space approach to reduce the dimensionality of the fitting problem and a non-linear regression technology to interpolate among hearing aid parameter settings. This listener-driven method provides not only a technique for preferred aid fitting, but also information on individual differences and the effects of gain compensation on different musical styles.

Abstract: A system for hearing assistance devices to assist hearing aid fitting applied to individual differences in hearing impairment. The system is also usable for assisting fitting and use of hearing assistance devices for listeners of music. The method uses a subjective space approach to reduce the dimensionality of the fitting problem and a non-linear regression technology to interpolate among hearing aid parameter settings. This listener-driven method provides not only a technique for preferred aid fitting, but also information on individual differences and the effects of gain compensation on different musical styles.

Abstract: A system for hearing assistance devices to assist hearing aid fitting applied to individual differences in hearing impairment. The system is also usable for assisting fitting and use of hearing assistance devices for listeners of music. The method uses a subjective space approach to reduce the dimensionality of the fitting problem and a non-linear regression technology to interpolate among hearing aid parameter settings. This listener-driven method provides not only a technique for preferred aid fitting, but also information on individual differences and the effects of gain compensation on different musical styles.

Abstract: A system for hearing assistance devices to assist hearing aid fitting applied to individual differences in hearing impairment. The system is also usable for assisting fitting and use of hearing assistance devices for listeners of music. The method uses a subjective space approach to reduce the dimensionality of the fitting problem and a non-linear regression technology to interpolate among hearing aid parameter settings. This listener-driven method provides not only a technique for preferred aid fitting, but also information on individual differences and the effects of gain compensation on different musical styles.

Abstract: A system for hearing assistance devices to assist hearing aid fitting applied to individual differences in hearing impairment. The system is also usable for assisting fitting and use of hearing assistance devices for listeners of music. The method uses a subjective space approach to reduce the dimensionality of the fitting problem and a non-linear regression technology to interpolate among hearing aid parameter settings. This listener-driven method provides not only a technique for preferred aid fitting, but also information on individual differences and the effects of gain compensation on different musical styles.