Technologies for automatic speech recognition using articulatory parameters are disclosed. An automatic speech recognition device may capture speech data from a speaker and also capture an image of the speaker. The automatic speech recognition device may determine one or more articulatory parameters based on the image, such as such as a jaw angle, a lip protrusion, or a lip height, and compare those parameters with articulatory parameters of training users. After selecting training users with similar articulatory parameters as the training speaker, the automatic speech recognition device may select training data associated with the selected training speakers, including parameters to use for an automatic speech recognition algorithm. By using the parameters already optimized for training users with similar articulatory parameters as the speaker, the automatic speech recognition device may quickly adapt an automatic speech recognition algorithm to the speaker.

The present invention relates to systems and methods for characterizing at least one anatomical parameter of an upper airway of a patient by analysing spectral properties of an utterance, comprising: a mechanical coupler comprising means for restricting the jaw position of the patient; means for recording an utterance; and processing means for determining at least one anatomical parameter of the upper airway from the recorded utterance and comparing the recorded utterance to a threshold value. In addition the present invention relates to the use of the above mentioned systems as a diagnostics tool for assessing obstructive sleep apnea.

An apparatus or method to allow a user to control an audio processing operation of an internal and/or external microphone(s). The method includes providing a configurable user interface which enables mixing of audio signals through interaction with the user interface. The audio signals may be captured with internal or external micorphones.

An apparatus or method to allow a user to control an audio processing operation of an internal and/or external microphone(s). The method includes providing a configurable user interface which enables mixing of audio signals through interaction with the user interface. The audio signals may be captured with internal or external micorphones.

Provided are methods and systems of encoding and decoding speech from a subject using articulatory physiology. Methods of the present disclosure include receiving a physiological feature signal associated with a spatiotemporal movement of a vocal tract articulator, generating a speech pattern signal in response to the physiological feature signal, and outputting speech that is based on the speech pattern signal. Methods of the present disclosure further include acquiring one or more of a linguistic signal and an acoustic signal; associating a physiological feature with the linguistic or acoustic signal; generating a speech pattern signal in response to the physiological feature; and outputting speech that is based on the speech pattern signal. Speech decoding systems and devices using articulatory physiology for practicing the subject methods are also provided. Various steps and aspects of the methods will now be described in greater detail below.

Provided are methods and systems of encoding and decoding speech from a subject using articulatory physiology. Methods of the present disclosure include receiving a physiological feature signal associated with a spatiotemporal movement of a vocal tract articulator, generating a speech pattern signal in response to the physiological feature signal, and outputting speech that is based on the speech pattern signal. Methods of the present disclosure further include acquiring one or more of a linguistic signal and an acoustic signal; associating a physiological feature with the linguistic or acoustic signal; generating a speech pattern signal in response to the physiological feature; and outputting speech that is based on the speech pattern signal. Speech decoding systems and devices using articulatory physiology for practicing the subject methods are also provided. Various steps and aspects of the methods will now be described in greater detail below.

Various embodiments of the present invention describe systems and techniques for producing sounds similar to a user's internal perception of the user's voice. In various embodiments, systems and methods may be disclosed. The systems and methods may be configured to receive first sound data associated with a user, determine a transformation based on the first sound data, create a novel utterance based on the first sound data and the transformation, where the novel utterance approximates an internal perception of the user's self-produced speech, and cause a speaker to output the novel utterance.

Various embodiments of the present invention describe systems and techniques for producing sounds similar to a user's internal perception of the user's voice. In various embodiments, systems and methods may be disclosed. The systems and methods may be configured to receive first sound data associated with a user, determine a transformation based on the first sound data, create a novel utterance based on the first sound data and the transformation, where the novel utterance approximates an internal perception of the user's self-produced speech, and cause a speaker to output the novel utterance.

An emotion estimation apparatus 1 includes: a generation unit 2 configured to generate acoustic characteristic information indicating an acoustic characteristic using a first acoustic signal output to the ear canal and a second acoustic signal produced by the first acoustic signal echoing inside the body; and an estimation unit 3 configured to estimate emotion using the acoustic characteristic information.

An emotion estimation apparatus 1 includes: a generation unit 2 configured to generate acoustic characteristic information indicating an acoustic characteristic using a first acoustic signal output to the ear canal and a second acoustic signal produced by the first acoustic signal echoing inside the body; and an estimation unit 3 configured to estimate emotion using the acoustic characteristic information.