Abstract: A classification apparatus is configured to perform a classification using a neural network with at least one hidden layer and an output layer, wherein the classification apparatus comprises a coarse training unit configured to train the neural network on a subset of neurons of a last hidden layer and a set of neurons of the output layer; and a fine training unit configured to train the neural network on a set of the last hidden layer and a subset of neurons of the output layer. By executing the classification apparatus, training of a classification model can be improved by reducing the computational burden of the classification, speeding up the training time of a classification model, and speeding up the inference time during application of the classification model.

Abstract: Systems and methods for accent and dialect modification are disclosed. Discussed are a method for selecting a target dialect and accent to use to modify voice communications based on a context and a method for selectively modifying one or more words in voice communications in one dialect and accent with one or more vocal features of a different accent.

Abstract: Systems and methods for detection, classification, and diagnosis of vocal anomalies in vocal streams are disclosed. Discussed are a method for generating a biometric voiceprint for analyzing user vocal streams to detect and classify vocal anomalies and a method for notifying the appropriate party, where the notification is based on the diagnosis reported by the system. Manual classification in the event of automatic classification failure is discussed, where the manual classification data can be used as training data to improve the functionality of the classification model.

Abstract: Embodiments of the present disclosure describe a call recording system and a call recording method for automatically recording, i.e. storing, a call candidate when an active call is detected. The call recording system comprises a sound receiver to receive sound data and to convert sound data to audio representations of sound, a buffer to buffer the audio representations of sound for a predetermined time duration, a call candidate determination unit to determine if the buffered audio representations comprise a call candidate, a call analyzer to analyze the call candidate, wherein the call analyzer determines if the call candidate is a call to be stored, and a storage to store the call candidate as a call. Hence, a reliable system can be provided for automatically storing a call.

Abstract: A method includes using a computing platform to extract audio and video segments from current video data of a person; apply a first trained supervised machine learning (ML) model to the video segment to produce a first probability distribution of emotional states of the person; and apply a second trained supervised ML model to the audio segment to produce a second probability distribution of the emotional states of the person. The first and second probability distributions are used by the computing platform to produce a third probability distribution of mismatch-based emotional states of the person. The third probability distribution is based on mismatches between the first and second probability distributions.

Abstract: Systems and methods for accent and dialect modification are disclosed. Discussed are a method for selecting a target dialect and accent to use to modify voice communications based on a context and a method for selectively modifying one or more words in voice communications in one dialect and accent with one or more vocal features of a different accent.

Abstract: Systems and methods for accent and dialect modification are disclosed. Discussed are a method for selecting a target dialect and accent to use to modify voice communications based on a context and a method for selectively modifying one or more words in voice communications in one dialect and accent with one or more vocal features of a different accent.

Abstract: Systems and methods for accent and dialect modification are disclosed. Discussed are a method for selecting a target dialect and accent to use to modify voice communications based on a context and a method for selectively modifying one or more words in voice communications in one dialect and accent with one or more vocal features of a different accent.

Abstract: An audio interface device, comprising: an interface unit and a wireless unit, wherein the interface unit is configured to relay a first audio signal transmitted between a microphone and a communication device and a second audio signal transmitted between the communication device and a speaker, and to route first audio data related to the first audio signal and second audio data related to the second audio signal to the wireless unit; and wherein the wireless unit is configured to transmit the first audio data and the second audio data to a remote audio device.

Abstract: An audio interface device, comprising: an interface unit and a wireless unit, wherein the interface unit is configured to relay a first audio signal transmitted between a microphone and a communication device and a second audio signal transmitted between the communication device and a speaker, and to route first audio data related to the first audio signal and second audio data related to the second audio signal to the wireless unit; and wherein the wireless unit is configured to transmit the first audio data and the second audio data to a remote audio device.

Abstract: Embodiments of the present disclosure describe a call recording system and a call recording method for automatically recording, i.e. storing, a call candidate when an active call is detected. The call recording system comprises a sound receiver to receive sound data and to convert sound data to audio representations of sound, a buffer to buffer the audio representations of sound for a predetermined time duration, a call candidate determination unit to determine if the buffered audio representations comprise a call candidate, a call analyzer to analyze the call candidate, wherein the call analyzer determines if the call candidate is a call to be stored, and a storage to store the call candidate as a call. Hence, a reliable system can be provided for automatically storing a call.